Automated vehicle repair estimation by voting ensembling of multiple artificial intelligence functions is provided. A method comprises receiving a plurality of vehicle repair recommendation sets, each identifying (i) at least one component of a damaged vehicle, (ii) a recommended vehicle repair operation for each identified component, and (iii) a score and/or confidence percentage for each operation; when a plurality of the sets identify recommended operations for one of the components, selecting the operation having the highest score, and unselecting the other operations for the component; generating a composite vehicle repair recommendation set, wherein the composite vehicle repair recommendation set identifies the selected recommended vehicle repair operation, and wherein the composite vehicle repair recommendation set does not identify the unselected recommended vehicle repair operation; and providing the composite vehicle repair recommendation set to one or more claims management systems.
A computer-implemented method for adjusting one or more electronic medical bills for a claimant injured in an accident comprises generating a user interface to be presented to a claims adjuster; receiving a first user input identifying a claimant; responsive to the first user input, retrieving and aggregating multiple electronic medical bills each having at least one line; generating one or more findings and multiple scenarios by providing the aggregated electronic medical bills as inference input to a trained machine learning model, wherein the trained machine learning model has been trained with historical electronic medical bills and corresponding findings and scenarios, wherein responsive to the inference input, the trained machine learning model outputs the one or more findings and the multiple scenarios, wherein the one or more findings represent rationales for approving, denying, or repricing, and wherein the multiple scenarios include cost estimates based on the one or more findings.
A computer-implemented method comprises obtaining an electronic claim record comprising claim data describing damage to a vehicle; selecting one or more of an obtained plurality of electronic vehicle diagnostic records by applying the records and claim data as inputs to a trained machine learning model, wherein responsive to the inference input the trained machine learning model selects one or more of the records; obtaining a vehicle repair estimate data structure having a plurality of fields; populating the fields of the vehicle repair estimate data structure with at least one of the claim data and the vehicle data from the selected one or more electronic vehicle diagnostic records; and generating a user interface for presentation to a user on a user device, wherein the user interface includes display elements that represent the populated fields of the generated vehicle repair estimate data structure.
Systems and methods are provided for a dynamic and iterative process for determining a weighted decision using a combination of weighted output from multiple, trained machine learning (ML) models. Key data can be identified and efficient decision-based processing can be achieved. In some examples, the system calculates a weighted decision of a repair or total loss determination for a motor vehicle, yet any industry or data set may be implemented with the use of the dynamic and iterative decision process.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
5.
COMPREHENSIVE LIABILITY MANAGEMENT PLATFORM WITH INTEGRATION WITH PROVIDER NETWORKS AND PROVIDER NEGOTIATIONS SYSTEMS
A computer-implemented method comprises: receiving, from an insurer system, an electronic medical bill; generating a decision representing a workflow selected from a plurality of the workflows based on at least one of a plurality of decisioning factors describing the electronic medical bill by providing the electronic medical bill as an inference input to a trained machine learning model, wherein responsive to the inference input the trained machine learning model generates the decision representing a workflow, wherein the trained machine learning model has been trained with historical electronic medical bills and corresponding historical decisions, the workflows including a provider network workflow and a provider negotiations workflow, and routing the electronic medical bill accordingly.
A computer-implemented method comprises receiving an image of a vehicle having damage to a first exterior body panel; providing the image to one or more trained machine learning models that are configured to identify a first region of the first exterior body panel to be repaired and a second region to be paint-blended, when the second region contains a second exterior body panel of the vehicle other than the first exterior body panel, generating an exterior body panel repainting list that includes the identification of the first exterior body panel of the vehicle and the identification of the second exterior body panel of the vehicle; querying a repainting cost database using the exterior body panel repainting list; and receiving a repainting cost estimate from the repainting cost database responsive to the querying.
A computer-implemented method comprises obtaining an image of a first damaged vehicle; selecting a set of images of second damaged vehicles that are similar to the first damaged vehicle; finding a set of images of the second vehicles showing damage similar to the damage to the first vehicle; obtaining a set of vehicle repair claims corresponding to the set of one or more images of the second vehicles; adding a selected subset to a repair estimate data structure; presenting a user interface that represents the selected subset of line items; receiving first user input that represents line items chosen by the user; generating a vector that represents the chosen line items; and applying the vector to a trained machine learning model, wherein the trained machine learning model outputs a refined subset of line items.
A computer-implemented method comprises: generating a user interface operable by a user to generate one or more vehicle repair estimate lines for repairing a damaged vehicle and/or request an automated review of the line(s); generating one or more first vehicle repair estimate lines, adding the one or more first vehicle repair estimate lines to a vehicle repair estimate data structure, and presenting a first view of the data structure in the user interface; obtaining images of the damaged vehicle, providing the images to one or more trained machine learning (ML) models, which provide first output comprising second vehicle repair estimate lines for the vehicle repair estimate, adding second vehicle repair estimate lines to the data structure, and presenting a second view of the data structure in the user interface; and generating a vehicle repair estimation document based on the vehicle repair estimate data structure.
A computer-implemented method comprises obtaining an electronic claim record comprising claim data describing damage to a vehicle; selecting one or more of an obtained plurality of electronic vehicle diagnostic records by applying the records and claim data as inputs to a trained machine learning model, wherein responsive to the inference input the trained machine learning model selects one or more of the records; obtaining a vehicle repair estimate data structure having a plurality of fields; populating the fields of the vehicle repair estimate data structure with at least one of the claim data and the vehicle data from the selected one or more electronic vehicle diagnostic records; and generating a user interface for presentation to a user on a user device, wherein the user interface includes display elements that represent the populated fields of the generated vehicle repair estimate data structure.
A computer-implemented method comprises receiving an image of a vehicle having damage to a first exterior body panel; providing the image to one or more trained machine learning models that are configured to identify a first region of the first exterior body panel to be repaired and a second region to be paint-blended, when the second region contains a second exterior body panel of the vehicle other than the first exterior body panel, generating an exterior body panel repainting list that includes the identification of the first exterior body panel of the vehicle and the identification of the second exterior body panel of the vehicle; querying a repainting cost database using the exterior body panel repainting list; and receiving a repainting cost estimate from the repainting cost database responsive to the querying.
A computer-implemented method comprises obtaining an image of a first damaged vehicle; selecting a set of images of second damaged vehicles that are similar to the first damaged vehicle; finding a set of images of the second vehicles showing damage similar to the damage to the first vehicle; obtaining a set of vehicle repair claims corresponding to the set of one or more images of the second vehicles; adding a selected subset to a repair estimate data structure; presenting a user interface that represents the selected subset of line items; receiving first user input that represents line items chosen by the user; generating a vector that represents the chosen line items; and applying the vector to a trained machine learning model, wherein the trained machine learning model outputs a refined subset of line items.
A computer-implemented method comprises: generating a user interface operable by a user to generate one or more vehicle repair estimate lines for repairing a damaged vehicle and/or request an automated review of the line(s); generating one or more first vehicle repair estimate lines, adding the one or more first vehicle repair estimate lines to a vehicle repair estimate data structure, and presenting a first view of the data structure in the user interface; obtaining images of the damaged vehicle, providing the images to one or more trained machine learning (ML) models, which provide first output comprising second vehicle repair estimate lines for the vehicle repair estimate, adding second vehicle repair estimate lines to the data structure, and presenting a second view of the data structure in the user interface; and generating a vehicle repair estimation document based on the vehicle repair estimate data structure.
Systems and methods are provided for a dynamic and iterative process for determining a weighted decision using a combination of weighted output from multiple, trained machine learning (ML) models. Key data can be identified and efficient decision-based processing can be achieved. In some examples, the system calculates a weighted decision of a repair or total loss determination for a motor vehicle, yet any industry or data set may be implemented with the use of the dynamic and iterative decision process.
A new automotive collision repair technology is provided, including system and data flow architectures that are designed to provide enhanced data and enhanced data flow in the context of vehicle diagnosis and repair, particularly when repairs are necessary due to collisions. In some examples, the data flow through the network is streamlined, to avoid network congestion, to use fewer computer and network resources and/or to enable the utilization of smaller databases. In other examples, enhanced access to data in real-time and near real-time enabled by a Workflow Module supports more accurate and timely decisions on vehicle repair. An advantage of this new automotive collision repair technology is that it enables proper and proven repairs, which in turns increases operation safety of repaired vehicle and people safety.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G06Q 10/20 - Administration of product repair or maintenance
Vehicle insurance claim data is categorized into a plurality of strata. The categorized vehicle insurance claim data is mapped to corresponding geographic regions and aggregated. When the number of samples in the aggregated data meets a sampling threshold size, the aggregated data is clustered into clusters based on certain criteria and sampled to generate component synthetic peer data sets. A synthetic peer data set is generated by applying a bootstrap aggregation machine learning algorithm on the plurality of component synthetic peer data sets. The performance of a target vehicle insurance company is analyzed by comparing target vehicle insurance claim data of the target vehicle insurance company with the synthetic peer data set. The results of the comparison between the target vehicle insurance claim data and the synthetic peer are presented in a graphical representation.
A method and computing apparatus for determining comprehensive vehicle information using an intelligent Vehicle Identification Number (“VIN”) decoder process is described. The method and computing apparatus obtains OEM marketing data, OEM engineering data, parts catalog data, uses a machine learning algorithm to determine relational dependencies between the obtained OEM data and standard comprehensive vehicle configuration data to generate complete vehicle data using VIN.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
A method and computing apparatus for determining comprehensive vehicle information using an intelligent Vehicle Identification Number ("VIN") decoder process is described. The method and computing apparatus obtains OEM marketing data, OEM engineering data, parts catalog data, uses a machine learning algorithm to determine relational dependencies between the obtained OEM data and standard comprehensive vehicle configuration data to generate complete vehicle data using VIN.
A method, non-transitory computer readable medium, and apparatus that identifies one of a plurality of diagnostic mapping tables based on a diagnostic code associated with one of a plurality of data environment formats in an electronic claim. The diagnostic code associated with one of the plurality of data environment formats is correlated to at least one of a plurality of parts and laterality associated with another one of the plurality of data environment formats based on the identified one of the plurality of diagnostic code mapping tables. One of a plurality of assessment ratings is determined based on the diagnostic code the correlated one of the plurality of parts and the laterality, and a categorization table associated with the another one of the plurality of data environment formats. Execution of one of a plurality of actions on the electronic claim in response to the determined one of the plurality of assessment ratings for the diagnostic code is initiated.
In general, one aspect disclosed features a system, comprising: a hardware processor; and a non-transitory machine-readable storage medium encoded with instructions executable by the hardware processor to perform operations comprising: receiving an electronic record, the electronic record representing a medical bill, the medical bill comprising a plurality of attributes; mapping each attribute in the medical bill to a single bucket of a predetermined second quantity of the buckets according to a predetermined correspondence between the attributes and the buckets, the first quantity exceeding the second quantity; and providing identifiers of the single buckets as input to a machine learning model, the machine learning model being trained according to historical correspondences between the buckets and decisions of whether human review was necessary, wherein responsive to the input, the machine learning model provides as output an indication of whether the medical bill should be reviewed by a human.
A method for automatically determining injury treatment relation to a motor vehicle accident comprises obtaining a plurality of images of a damaged motor vehicle, vehicle data describing the motor vehicle, occupant data describing an occupant who occupied the motor vehicle during the motor vehicle accident, and injury data from an electronic insurance claim associated with the motor vehicle accident, the injury data specifying an injury to the occupant; determining a delta velocity value for the damaged motor vehicle by applying a first machine learning model to the set of images of the damaged motor vehicle and the vehicle data; determining an injury severity score by applying a second machine learning model to the delta velocity value for the damaged motor vehicle, the vehicle data, and the occupant data; and automatically adjudicating the electronic insurance claim.
G06T 7/246 - Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
G06V 10/70 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning
G06V 10/74 - Image or video pattern matching; Proximity measures in feature spaces
G06V 10/94 - Hardware or software architectures specially adapted for image or video understanding
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
21.
METHODS FOR ANALYZING INSURANCE DATA AND DEVICES THEREOF
Vehicle insurance claim data is categorized into a plurality of strata. The categorized vehicle insurance claim data is mapped to corresponding geographic regions and aggregated. When the number of samples in the aggregated data meets a sampling threshold size, the aggregated data is clustered into clusters based on certain criteria and sampled to generate component synthetic peer data sets. A synthetic peer data set is generated by applying a bootstrap aggregation machine learning algorithm on the plurality of component synthetic peer data sets. The performance of a target vehicle insurance company is analyzed by comparing target vehicle insurance claim data of the target vehicle insurance company with the synthetic peer data set. The results of the comparison between the target vehicle insurance claim data and the synthetic peer are presented in a graphical representation.
Systems, non-transitory machine-readable storage media, and computer-implemented methods are provided for automated scheduling of vehicle repair reinspections. In general, one aspect disclosed features a computer-implemented method comprising: obtaining an appraisal schedule that includes a plurality of appraisal appointments for appraisers, wherein each appointment identifies one of the appraisers, a vehicle repair to be appraised; receiving a reinspection notification that identifies a vehicle repair to be reinspected, a vehicle repair facility, and a duration for the reinspection; identifying availabilities in the appraisal schedule; selecting one of the availabilities in the appraisal schedule according to a predetermined assignment profile; modifying the appraisal schedule to schedule the reinspection during the selected availability, and sending an electronic message to an electronic device associated with the corresponding vehicle repair facility, wherein the electronic message identifies the vehicle repair to be reinspected, and the time of selected availability for the reinspection.
Systems, non-transitory machine-readable storage media, and computer- implemented methods are provided for automated scheduling of vehicle repair reinspections. In general, one aspect disclosed features a computer- implemented method comprising: obtaining an appraisal schedule that includes a plurality of appraisal appointments for appraisers, wherein each appointment identifies one of the appraisers, a vehicle repair to be appraised; receiving a reinspection notification that identifies a vehicle repair to be reinspected, a vehicle repair facility, and a duration for the reinspection; identifying availabilities in the appraisal schedule; selecting one of the availabilities in the appraisal schedule according to a predetermined assignment profile; modifying the appraisal schedule to schedule the reinspection during the selected availability, and sending an electronic message to an electronic device associated with the corresponding vehicle repair facility, wherein the electronic message identifies the vehicle repair to be reinspected, and the time of selected availability for the reinspection.
24.
AUTOMATED SELECTION OF VEHICLE REPAIRS FOR REINSPECTION
Systems, non-transitory machine-readable storage media, and computer- implemented methods are provided for automated selection of vehicle repairs for reinspection. In general, one aspect disclosed features a computer-implemented method comprising: receiving a notification that a vehicle repair estimate for a vehicle has been submitted by a vehicle repair facility; responsive to receiving the notification, determining whether the vehicle repair facility has satisfied a quantitative vehicle repair re-inspection benchmark; responsive to determining the vehicle repair facility has not satisfied the vehicle repair re-inspection benchmark, determining whether the vehicle repair facility has satisfied a temporal vehicle repair benchmark for repair of the vehicle; and responsive to determining the vehicle repair facility has satisfied the temporal vehicle repair benchmark for repair of the vehicle, initiating a re-inspection of the vehicle.
Systems and methods are provided for integrating damage evidence with appraisal management system to create a unified user experience for improving a virtual damage appraisal process. The system may display a curated collection of evidence providing an overview of the vehicle and sections of a vehicle damaged during an adverse incident. A user may select a damaged section from a plurality of damaged sections to view damage evidence determined by machine learning algorithms to best reflect the selected damaged section may be displayed. The damage evidence may be displayed concurrently with vehicle part selection and repair line editing functionality in a configurable graphical user interface (GUI) of a virtual appraisal application. Additionally, the system may generate set of recommendations for repairing or replacing the damaged parts in the selected section. The user may add the recommendations to a repair estimate as repair estimate lines.
Systems and methods are provided for integrating damage evidence with appraisal management system to create a unified user experience for improving a virtual damage appraisal process. The system may display a curated collection of evidence providing an overview of the vehicle and sections of a vehicle damaged during an adverse incident. A user may select a damaged section from a plurality of damaged sections to view damage evidence determined by machine learning algorithms to best reflect the selected damaged section may be displayed. The damage evidence may be displayed concurrently with vehicle part selection and repair line editing functionality in a configurable graphical user interface (GUI) of a virtual appraisal application. Additionally, the system may generate set of recommendations for repairing or replacing the damaged parts in the selected section. The user may add the recommendations to a repair estimate as repair estimate lines.
Systems and methods for processing paper bills are provided. In general, one aspect disclosed features a computer-implemented method, comprising: at a first computing device: receiving first data to be printed as text on a first form, encoding the received first data as a two-dimensional machine-readable code, and causing the first form to be printed on paper, including the text and the two-dimensional machine-readable code; and at a second computing device: receiving second data representing a scan of the printed two-dimensional machine-readable code, obtaining the first data from the received second data, and populating a second form according to the obtained first data.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
G06K 19/06 - Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code
G06K 15/02 - Arrangements for producing a permanent visual presentation of the output data using printers
A method and computing apparatus for automatically identifying whether or not one or more identified injuries are related to the insurance claim which has been submitted is described. The method and computing apparatus identify injury data in an electronic medical claim data associated with a claimant based diagnosis code data, uses a classifier to determine an association between the identified injury data represented by the diagnosis code data and the initial injury data represented by the initial diagnosis code data is identified when historical claim data is determined to be present for the claimant.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
29.
SYSTEMS AND METHODS FOR MANAGING REPAIR PROCEDURES FROM DISPARATE SOURCES
Systems and methods are provided for automating the process of cataloging repair documents published by Original Equipment Manufacturers (OEMs). The method determines a corresponding service repair vehicle for the OEM vehicle associated with eh repair documents. Further, the OEM repair instructions are associated with the one or more vehicle parts of a service repair vehicle identified in a repair estimate record. The method of cataloging repair procedures from various OEMs utilizes standardized naming conventions a database structure for uploading individual documents.
Systems and methods are provided for automating the process of determining non-reusable parts associated with replacement or repair of a primary part of a vehicle involved in a collision event. The primary parts to be repaired may be indicated in repair estimate record. Notably, replacement of some primary parts may require replacement of certain non-reusable parts (NRPs) that were not damaged during the collision event and are not identified as such. The method determines which NRPs are required to be replaced when repairing the primary damaged part by using repair documents specifying repair instructions for repairing the primary part. Further, the repair estimate record is updated to include the information related to the primary pars and their associated NRPs.
B60S 5/00 - Servicing, maintaining, repairing, or refitting of vehicles
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
System and methods for automated claim processing with endnote hierarchy are provided. In some embodiments, a computer-implemented method comprises: receiving an insurance claim, wherein the insurance claim comprises at least one line, and wherein each line comprises at least one procedure code and at least one explanation code; determining a first hierarchical rank of a plurality of the hierarchical ranks for a first explanation code in a first line based on predetermined associations between the explanation codes and the hierarchical ranks; determining, according to the determined first hierarchical rank for the first explanation code, whether the first line comprising the first code should be modified; modifying the first line comprising the first explanation code when it is determined that the first line comprising the first explanation code should be modified; and outputting the insurance claim after determining whether the first line comprising the first explanation code should be modified.
Systems and methods are provided for automating the process of determining non- reusable parts associated with replacement or repair of a primary part of a vehicle involved in a collision event. The primary parts to be repaired may be indicated in repair estimate record. Notably, replacement of some primary parts may require replacement of certain non-reusable parts (NRPs) that were not damaged during the collision event and are not identified as such. The method determines which NRPs are required to be replaced when repairing the primary damaged part by using repair documents specifying repair instructions for repairing the primary part. Further, the repair estimate record is updated to include the information related to the primary pars and their associated NRPs.
09 - Scientific and electric apparatus and instruments
16 - Paper, cardboard and goods made from these materials
35 - Advertising and business services
36 - Financial, insurance and real estate services
42 - Scientific, technological and industrial services, research and design
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
45 - Legal and security services; personal services for individuals.
Goods & Services
(1) Downloadable computer software and mobile application software for medical bill review, auditing and work flow management; downloadable computer software and mobile application software for medical and health-care cost review and cost management, insurance claims adjusting, and managing insurance claims and settlements; downloadable computer software and mobile application software for insurance claim analysis in the fields of auto casualty, worker's compensation, vehicle repair and vehicle repair estimating; downloadable computer software and mobile application software for the management of vehicle collision and vehicle repair businesses; downloadable computer database featuring automotive repair, diagnostic and estimating information; downloadable software application for employers to conduct health screening
(2) Automobile collision and repair estimating manuals (1) Business services, namely, providing business analysis and information regarding the management, processing, and administration of insurance claims; arranging of managed care contractual services in the fields of diagnostic imaging, home health care, durable medical equipment, specialty pharmacy, diagnostic lab services, and provider networks; business consulting services in the field of medical bill review, and providing insurance reimbursement recommendations to others; medical cost management; medical utilization and review services; medical cost containment; managed care services, namely, electronic processing of health care information, utilization review and pre-certification services, and review of medical bills for appropriate utilization; logistics management services in the field of workers' compensation insurance, namely, planning and coordinating specialized medical equipment, in-home health care, medical diagnostic services, accessibility specialists and contractors, sub-acute and detoxification, translation, and transportation services for injured individuals; medical bill management services, namely, receiving, data entering, and re-pricing of transactions that are originated by physicians, hospitals, and ancillary medical care providers; business networking services, namely, selecting, credentialing, contracting, monitoring and maintaining ongoing relationships with physicians, hospitals, and ancillary medical care providers; administration of pharmacy utilization programs, namely, pharmaceutical cost management and drug utilization review services; provision of business information and business analysis concerning medical utilization and pharmacy benefits of individuals and their workers' compensation, automobile insurance and pain management treatment claims; physician referrals
(2) Pharmacy benefit management services; pharmacy benefit claims administration; insurance and medical provider claims management and processing services; insurance services in the nature of loss control management for others; preferred provider network programs, namely, administration, review, and repricing of medical services provided through a network of health care providers under a workers' compensation or automobile insurance plan; providing information regarding workers' compensation or automobile recommended medical reimbursements; providing information used in the processing of workers' compensation and automobile claims
(3) Providing temporary use of non-downloadable web-based software applications for use in the management, administration and processing of auto physical damage claims and auto glass replacement claims; providing temporary use of on-line non-downloadable software featuring repair data and procedures for assessing or repairing damaged vehicles; providing temporary use of non-downloadable web-based software applications for use in the management, processing and administration of insurance claims; providing on-line non-downloadable software for identifying, correcting and adjusting billing and coding errors in medical claims
(4) Medical assistance services; providing medical, health and wellness information
(5) Case management services, namely, the coordination of necessary medical services, vocational issues and educational services for persons injured at work
34.
Systems and methods for automating mapping of repair procedures to repair information
Systems and methods are provided for automating the process of mapping repair documents, published by Original Equipment Manufacturers (OEMs), to repair information provided in a repair estimate record. A baseline set of repair estimate records specifying one or more parts of a baseline vehicle and an associated set of repair documents specifying instructions for repairing the one or more parts of the baseline vehicle may be saved using a data categorization model in a mapping dataset. The repair documents associated with baseline set of repair estimate records which have been saved in the mapping dataset may then be used to automatically determine associations between another set of repair estimate records and corresponding repair documents.
Vehicle repair workflow automation with natural language processing is disclosed. One computer-implemented method comprises: providing images of a damaged vehicle as first input to a computer vision machine learning model, wherein the computer vision machine learning model has been trained with images of other damaged vehicles and corresponding vehicle repair operations; receiving first output of the computer vision machine learning model responsive to the first input, wherein the first output represents a plurality of the vehicle repair operations; providing the first output of the computer vision machine learning model to a natural language processing (NLP) machine learning model, wherein the NLP machine learning model has been trained with vehicle repair content comprising a plurality of vehicle repair procedures; and receiving second output of the NLP machine learning model responsive to the second input, wherein the second output comprises a recommended one of the plurality of the vehicle repair procedures.
Vehicle repair workflow automation with natural language processing is disclosed. One computer-implemented method comprises: providing images of a damaged vehicle as first input to a computer vision machine learning model, wherein the computer vision machine learning model has been trained with images of other damaged vehicles and corresponding vehicle repair operations; receiving first output of the computer vision machine learning model responsive to the first input, wherein the first output represents a plurality of the vehicle repair operations; providing the first output of the computer vision machine learning model to a natural language processing (NLP) machine learning model, wherein the NLP machine learning model has been trained with vehicle repair content comprising a plurality of vehicle repair procedures; and receiving second output of the NLP machine learning model responsive to the second input, wherein the second output comprises a recommended one of the plurality of the vehicle repair procedures.
Systems and methods are provided for automating the process of mapping repair documents, published by Original Equipment Manufacturers (OEMs), to repair information provided in a repair estimate record. A baseline set of repair estimate records specifying one or more parts of a baseline vehicle and an associated set of repair documents specifying instructions for repairing the one or more parts of the baseline vehicle may be saved using a data categorization model in a mapping dataset. The repair documents associated with baseline set of repair estimate records which have been saved in the mapping dataset may then be used to automatically determine associations between another set of repair estimate records and corresponding repair documents.
Systems and methods are provided for automating the process of mapping repair documents, published by Original Equipment Manufacturers (OEMs), to repair information provided in a repair estimate record. A baseline set of repair estimate records specifying one or more parts of a baseline vehicle and an associated set of repair documents specifying instructions for repairing the one or more parts of the baseline vehicle may be saved using a data categorization model in a mapping dataset. The repair documents associated with baseline set of repair estimate records which have been saved in the mapping dataset may then be used to automatically determine associations between another set of repair estimate records and corresponding repair documents.
Systems and methods are provided for automating the process of mapping repair documents, published by Original Equipment Manufacturers (OEMs), to repair information provided in a repair estimate record. A baseline set of repair estimate records specifying one or more parts of a baseline vehicle and an associated set of repair documents specifying instructions for repairing the one or more parts of the baseline vehicle may be saved using a data categorization model in a mapping dataset. The repair documents associated with baseline set of repair estimate records which have been saved in the mapping dataset may then be used to automatically determine associations between another set of repair estimate records and corresponding repair documents.
Systems and methods for managing predictions for vehicle repair estimates are provided. A method includes providing one or more images of a damaged vehicle as input to a machine learning model, wherein the machine learning model has been trained with images of other damaged vehicles and corresponding vehicle operations, wherein each of the vehicle operations represents the repair or replacement of a vehicle component; receiving output of the machine learning model responsive to the input, wherein the output comprises a plurality of values each corresponding to one of a plurality of the vehicle operations; determining a confidence metric based on the values; making a comparison between the confidence metric and a confidence threshold value; and selecting the one of the plurality of the vehicle operations corresponding to the highest value as a predicted operation based on the comparison.
Systems and methods for managing predictions for vehicle repair estimates are provided. A method includes providing one or more images of a damaged vehicle as input to a machine learning model, wherein the machine learning model has been trained with images of other damaged vehicles and corresponding vehicle operations, wherein each of the vehicle operations represents the repair or replacement of a vehicle component; receiving output of the machine learning model responsive to the input, wherein the output comprises a plurality of values each corresponding to one of a plurality of the vehicle operations; determining a confidence metric based on the values; making a comparison between the confidence metric and a confidence threshold value; and selecting the one of the plurality of the vehicle operations corresponding to the highest value as a predicted operation based on the comparison.
A vehicle repair estimating tool with near-real-time compliance is provided, In general, one aspect disclosed features a method comprising: providing a near-real-time view of a repair estimate record to a client device, the repair estimate record having one or more fields, receiving, from the client device, a data entry input to be applied to one of the fields of the repair estimate record, selecting, in near real time, one or more compliance rules related to the one of the fields responsive to receiving the data entry input, determining, in near real time, whether the data entry input is valid based on the selected one or more compliance rules, and when the data entry input is determined not to be valid, notifying the client device, in near real time, that the data entry input is not valid for the one of the fields.
A vehicle repair estimating tool with near-real-time compliance is provided, In general, one aspect disclosed features a method comprising: providing a near- real-time view of a repair estimate record to a client device, the repair estimate record having one or more fields, receiving, from the client device, a data entry input to be applied to one of the fields of the repair estimate record, selecting, in near real time, one or more compliance rules related to the one of the fields responsive to receiving the data entry input, determining, in near real time, whether the data entry input is valid based on the selected one or more compliance rules, and when the data entry input is determined not to be valid, notifying the client device, in near real time, that the data entry input is not valid for the one of the fields.
A near-real-time collaborative vehicle repair estimating tool is provided. In general, one aspect disclosed features a system, comprising: a hardware processor; and a non- transitory machine-readable storage medium encoded with instructions executable by the hardware processor to perform a method comprising: providing at least one view of a repair estimate record to a plurality of client devices; receiving a revision of the repair estimate record from one of the client devices; generating a revised repair estimate record by revising the repair estimate record according to the received revision responsive to receiving the revision of the repair estimate record; and providing at least one view of the revised repair estimate record to the plurality of client devices in near real time with receiving the revision of the repair estimate record.
45.
SYSTEMS AND METHODS FOR VEHICLE INTAKE FOR DAMAGED VEHICLES
In general, one aspect disclosed features a computer-implemented method comprising: obtaining an image related to a damaged vehicle; determining an image type of the image, wherein the image type describes an item contained in the image; extracting one or more images of text from the image; extracting one or more text strings from each image of text; identifying a type of each text string based on the determined image type; obtaining a record, and for each text string: selecting a field of the record based on the identified type of the text string, and populating the selected field with the text string; and determining an identity of the damaged vehicle based on the populated record.
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
46.
METHODS FOR AUTOMATING CUSTOMER AND VEHICLE DATA INTAKE USING WEARABLE COMPUTING DEVICES
Systems and methods are provided for automating information intake process by generating intake instructions for display on a client computing device. A user may be directed to capture data that includes vehicle and owner information using a wearable computing device. Insurance claim information, including damage information, may be obtained based on the captured vehicle information. The damage information may be used to determine intake instructions for capturing the images or videos of the damage. The user may use the system in a handsfree manner by viewing intake instructions via a display of the wearable computing device which allows the user to view the intake instructions while capturing the intake information. Additionally, the user may use voice commands or gestures to control the display of intake instructions.
09 - Scientific and electric apparatus and instruments
16 - Paper, cardboard and goods made from these materials
35 - Advertising and business services
36 - Financial, insurance and real estate services
42 - Scientific, technological and industrial services, research and design
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
45 - Legal and security services; personal services for individuals.
Goods & Services
Downloadable computer software and mobile application software for medical bill review, auditing and work flow management; downloadable computer software and mobile application software for medical and health-care cost review and cost management, insurance claims adjusting, and managing insurance claims and settlements; downloadable computer software and mobile application software for insurance claim analysis in the fields of auto casualty, worker's compensation, vehicle repair and vehicle repair estimating; downloadable computer software and mobile application software for the management of vehicle collision and vehicle repair businesses; downloadable electronic computer database featuring automotive repair, diagnostic and estimating information; downloadable computer software application for employers to conduct health screening Printed automobile collision and repair estimating manuals Business services, namely, providing business analysis and business information regarding the management, processing, and administration of insurance claims; arranging of managed care contractual services in the fields of diagnostic imaging, home health care, durable medical equipment, specialty pharmacy, diagnostic lab services, and medical provider networks services; business consulting services in the field of medical bill review, and insurance reimbursement recommendations for others; medical cost management; medical cost containment; managed care services, namely, electronic processing of health care information, utilization review and pre-certification services; logistics management services in the field of workers' compensation insurance, namely, planning and coordinating specialized medical equipment, in-home health care, medical diagnostic services, accessibility specialists and contractors, sub-acute and detoxification, translation, and transportation services for injured individuals; medical claims management services, namely, receiving, data entering, and re-pricing of transactions that are originated by physicians, hospitals, and ancillary medical care providers; business networking services, namely, maintaining ongoing relationships with physicians, hospitals, and ancillary medical care providers; administration of pharmacy utilization programs, namely, pharmaceutical cost management and drug utilization review services; provision of business information and business analysis concerning medical utilization and pharmacy benefits of individuals and their workers' compensation, automobile insurance and pain management treatment claims; physician referrals; Medical claims management services, namely, receiving, data entering, and re-pricing of transactions that are originated by physicians, hospitals, and ancillary medical care providers; preferred provider network programs, namely, medical claims management services in the nature of repricing of transactions that are originated by medical care provider services provided through a network of health care providers under a workers' compensation or automobile insurance plan Pharmacy benefit management services; pharmacy benefit insurance claims administration; insurance claims processing services; insurance services in the nature of loss control management for others; preferred provider network programs, namely, administration of medical services provided through a network of health care providers under a workers' compensation or automobile insurance plan; providing information regarding recommended policy rates for workers' compensation or automobile insurance claim medical reimbursements; providing information used in the processing of workers' compensation and automobile claims; Medical insurance case and utilization review and insurance claims adjustment services for healthcare purchasers and payors and providers Providing temporary use of non-downloadable web-based software applications for use in the management, administration and processing of auto physical damage claims and auto glass replacement claims; providing temporary use of on-line non-downloadable software featuring repair data and procedures for assessing or repairing damaged vehicles; providing temporary use of non-downloadable web-based software applications for use in the management, processing and administration of insurance claims; providing on-line non-downloadable software for identifying, correcting and adjusting billing and coding errors in medical claims Medical assistance services; providing medical, health and wellness information Case management services, namely, the coordination of necessary medical services, vocational issues and educational services for persons injured at work
45 - Legal and security services; personal services for individuals.
Goods & Services
Case management services, namely, the coordination of necessary medical services, vocational issues and educational services for persons injured at work
09 - Scientific and electric apparatus and instruments
16 - Paper, cardboard and goods made from these materials
35 - Advertising and business services
36 - Financial, insurance and real estate services
42 - Scientific, technological and industrial services, research and design
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
Goods & Services
(1) Downloadable computer software and mobile application software for medical bill review, auditing and work flow management; downloadable computer software and mobile application software for medical and health-care cost review and cost management, insurance claims adjusting, and managing insurance claims and settlements; downloadable computer software and mobile application software for insurance claim analysis in the fields of auto casualty, worker's compensation, vehicle repair and vehicle repair estimating; downloadable computer software and mobile application software for the management of vehicle collision and vehicle repair businesses; downloadable computer database featuring automotive repair, diagnostic and estimating information; downloadable software application for employee health screening
(2) Automobile collision and repair estimating manuals (1) Business services, namely, providing business analysis and information regarding the management, processing, and administration of insurance claims; arranging of managed care contractual services in the fields of diagnostic imaging, home health care, durable medical equipment, specialty pharmacy, diagnostic lab services, and healthcare network services; business consulting services in the field of medical invoice review, and providing insurance reimbursement recommendations to others; medical cost management; health care utilization and review services; health care cost containment; managed care services, namely, electronic processing of health care information, utilization review and pre-certification services, and review of health care claims for appropriate clinical management; logistics management services in the field of healthcare, namely, planning and coordinating specialized medical equipment, in-home health care, medical diagnostic services, accessibility specialists and contractors, sub-acute and detoxification, and transportation of people for others in the field of healthcare; medical claims management services, namely, receiving, data entering, and re-pricing of transactions that are originated by physicians, hospitals, and ancillary medical care providers; business networking services, namely, coordinating and facilitating through networks of patient care and goods vendors and providers; administration of pharmacy utilization programs, namely, pharmaceutical cost management and drug utilization review services; provision of business information and business analysis concerning healthcare benefits and pharmacy benefits of individuals and their workers' compensation, automobile insurance and pain management treatment claims; physician referrals
(2) Pharmacy benefit management services; pharmacy and healthcare benefit management consulting services; insurance claims administration; insurance and medical provider claims management and processing services; insurance services in the nature of loss control management for others; preferred provider network programs, namely, administration of medical benefits provided through a network of health care providers under a workers' compensation insurance plan; providing information regarding workers' compensation insurance policy rates; providing information in the field of workers' compensation
(3) Providing temporary use of non-downloadable web-based software applications for use in the management, administration and processing of auto physical damage claims and auto glass replacement claims; providing temporary use of on-line non-downloadable software featuring repair data and procedures for assessing or repairing damaged vehicles; providing temporary use of non-downloadable web-based software applications for use in the management, processing and administration of insurance claims; providing on-line non-downloadable software for identifying, correcting and adjusting billing and coding errors in medical claims
(4) Medical assistance services; providing medical, health and wellness information
50.
METHODS FOR MORE ACCURATELY MANAGING PROCESSING OF MEDICAL BILL DATA AND DEVICES THEREOF
Methods, non-transitory computer readable media, and computing apparatus that assist with more accurately managing processing of medical bill data includes identifying previously submitted bill data associated with received medical bill data from a client based on one or more service data parameters in the received medical bill data and the identified previously submitted bill data. The received medical bill data is determined to be erroneous medical bill data based on the identified previously submitted bill data and a time period between the previously submitted bill data and the received medical bill data. The received medical bill data is classified as a follow-up procedure bill data when the received medical bill data is determined to be an erroneous medical bill data. Compensation data is restricted for the received medical bill data classified as the follow-up procedure bill data.
A method, non-transitory computer readable medium, and apparatus that improves automated damage appraisal includes analyzing one or more obtained images of property using a deep neural network with multiple hidden layers of units between an input and output and which has stored knowledge data encoded from one or more stored property damage images to identify the part of the vehicle that has sustained damage. Damage data on an extent of the damage in the identified part of the vehicle is determined using the deep neural network which has stored knowledge data encoded from one or more stored property damage images. The identified generic part of the vehicle is used to obtain a corresponding Part ID Code by using a parts dictionary. Part Qualifier information obtained using VIN information is then used in conjunction with the Part ID to obtain the OEM-specific part and then generate one or more repair lines for the repair estimate.
A new automotive collision repair technology is provided, including system and data flow architectures that are designed to provide enhanced data and enhanced data flow in the context of vehicle diagnosis and repair, particularly when repairs are necessary due to collisions. In some examples, the data flow through the network is streamlined, to avoid network congestion, to use fewer computer and network resources and/or to enable the utilization of smaller databases. In other examples, enhanced access to data in real-time and near real-time enabled by a Workflow Module supports more accurate and timely decisions on vehicle repair. An advantage of this new automotive collision repair technology is that it enables proper and proven repairs, which in turns increases operation safety of repaired vehicle and people safety.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G06Q 10/20 - Administration of product repair or maintenance
A method, non-transitory computer readable medium, and apparatus that improves automated damage appraisal includes analyzing one or more obtained images of property using a deep neural network with multiple hidden layers of units between an input and output and which has stored knowledge data encoded from one or more stored property damage images to identify which area of the property has damage. Damage data on an extent of the damage in the identified area of the property is determined using the deep neural network which has stored knowledge data encoded from one or more stored property damage images. The identified damaged part and may be used to determine one or more adjacent parts based on the vehicle information and the repair operation type.
A computer-implemented method comprising: obtaining repair estimate data that describes a repair estimate for a damaged vehicle; extracting, from an OEM repair procedure database according to the received repair estimate data, repair procedure data that describes repair procedures for the damaged vehicle; transmitting the extracted repair procedure data to at least one technician computing device; obtaining repair log data generated by the at least one technician computing device, wherein the repair log data describes one or more repairs performed upon the damaged vehicle; determining whether the repair procedures for the damaged vehicle have been satisfactorily performed based on the received repair log data and the extracted repair procedure data; sending an electronic approval message responsive to determining the repair procedures for the damaged vehicle have been satisfactorily performed; and sending an electronic disapproval message responsive to determining the repair procedures for the damaged vehicle have not been satisfactorily performed.
G06Q 10/20 - Administration of product repair or maintenance
G06F 16/90 - Information retrieval; Database structures therefor; File system structures therefor - Details of database functions independent of the retrieved data types
G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
55.
Automated vehicle repair estimation by aggregate ensembling of multiple artificial intelligence functions
Automated vehicle repair estimation by aggregate ensembling of multiple artificial intelligence functions is provided. A method comprises receiving a plurality of vehicle repair recommendation sets for a damaged vehicle, wherein each of the vehicle repair recommendation sets identifies at least one recommended vehicle repair operation of a plurality of the vehicle repair operations for the damaged vehicle; aggregating a plurality of the recommended vehicle repair operations; generating a composite vehicle repair recommendation set that identifies the aggregated recommended vehicle repair operations; and providing the composite vehicle repair recommendation set to one or more vehicle repair insurance claims management systems.
Automated vehicle repair estimation by random ensembling of multiple artificial intelligence functions is provided. A method comprises receiving a vehicle damage object that includes a plurality of metadata objects of the damaged vehicle; fragmenting the object into fragments each including at least one of the metadata objects; providing each of the fragments to a respective artificial intelligence function; receiving a respective vehicle repair recommendation set from each of the artificial intelligence functions, wherein each of the vehicle repair recommendation sets identifies a recommended vehicle repair operation of a plurality of the vehicle repair operations for the damaged vehicle; selecting a plurality of the recommended vehicle repair operations; generating a composite vehicle repair recommendation set that identifies the selected recommended vehicle repair operations; and providing the composite vehicle repair recommendation set to one or more vehicle repair insurance claims management systems.
Automated vehicle repair estimation by voting ensembling of multiple artificial intelligence functions is provided. A method comprises receiving a plurality of vehicle repair recommendation sets, each identifying (i) at least one component of a damaged vehicle, (ii) a recommended vehicle repair operation for each identified component, and (iii) a score and/or confidence percentage for each operation; when a plurality of the sets identify recommended operations for one of the components, selecting the operation having the highest score, and unselecting the other operations for the component; generating a composite vehicle repair recommendation set, wherein the composite vehicle repair recommendation set identifies the selected recommended vehicle repair operation, and wherein the composite vehicle repair recommendation set does not identify the unselected recommended vehicle repair operation; and providing the composite vehicle repair recommendation set to one or more claims management systems.
Automated vehicle repair estimation by preferential ensembling of multiple artificial intelligence functions is provided. A method comprises receiving, from each source of a plurality of the sources, a respective vehicle repair recommendation set for a damaged vehicle, wherein each vehicle repair recommendation set identifies a recommended vehicle repair operation of a plurality of the vehicle repair operations for the damaged vehicle; determining a respective source rank of each source from a plurality of the source ranks; generating a composite vehicle repair recommendation set that identifies the recommended vehicle repair operations in an order determined according to the source ranks of the respective sources; and providing the composite vehicle repair recommendation set to one or more vehicle repair insurance claims management systems.
Automated vehicle repair estimation by adaptive ensembling of multiple artificial intelligence functions is provided. A method comprises receiving, from a plurality of sources, vehicle repair recommendation sets identifying recommended vehicle repair operations for damaged vehicle components; selecting, by a trained artificial intelligence function, one of the operations for each component based on a plurality of learned states; generating a composite vehicle repair recommendation set identifying the selected operation; providing the composite vehicle repair recommendation set to one or more claims management systems; and repeatedly retraining the trained artificial intelligence function by adjusting the learned states according to the vehicle damage objects received, and the corresponding composite vehicle repair recommendation generated, since the last retraining of the trained artificial intelligence function.
Automated vehicle repair estimation by preferential ensembling of multiple artificial intelligence functions is provided. A method comprises receiving, from each source of a plurality of the sources, a respective vehicle repair recommendation set for a damaged vehicle, wherein each vehicle repair recommendation set identifies a recommended vehicle repair operation of a plurality of the vehicle repair operations for the damaged vehicle; determining a respective source rank of each source from a plurality of the source ranks; generating a composite vehicle repair recommendation set that identifies the recommended vehicle repair operations in an order determined according to the source ranks of the respective sources; and providing the composite vehicle repair recommendation set to one or more vehicle repair insurance claims management systems.
A computer-implemented method comprising: obtaining repair estimate data that describes a repair estimate for a damaged vehicle; extracting, from an oem repair procedure database according to the received repair estimate data, repair procedure data that describes repair procedures for the damaged vehicle; transmitting the extracted repair procedure data to at least one technician computing device; obtaining repair log data generated by the at least one technician computing device, wherein the repair log data describes one or more repairs performed upon the damaged vehicle; determining whether the repair procedures for the damaged vehicle have been satisfactorily performed based on the received repair log data and the extracted repair procedure data; sending an electronic approval message responsive to determining the repair procedures for the damaged vehicle have been satisfactorily performed; and sending an electronic disapproval message responsive to determining the repair procedures for the damaged vehicle have not been satisfactorily performed.
Automated vehicle repair estimation by adaptive ensembling of multiple artificial intelligence functions is provided. A method comprises receiving, from a plurality of sources, vehicle repair recommendation sets identifying recommended vehicle repair operations for damaged vehicle components; selecting, by a trained artificial intelligence function, one of the operations for each component based on a plurality of learned states; generating a composite vehicle repair recommendation set identifying the selected operation; providing the composite vehicle repair recommendation set to one or more claims management systems; and repeatedly retraining the trained artificial intelligence function by adjusting the learned states according to the vehicle damage objects received, and the corresponding composite vehicle repair recommendation generated, since the last retraining of the trained artificial intelligence function.
Automated vehicle repair estimation by voting ensembling of multiple artificial intelligence functions is provided. A method comprises receiving a plurality of vehicle repair recommendation sets, each identifying (i) at least one component of a damaged vehicle, (ii) a recommended vehicle repair operation for each identified component, and (iii) a score and/or confidence percentage for each operation; when a plurality of the sets identify recommended operations for one of the components, selecting the operation having the highest score, and unselecting the other operations for the component; generating a composite vehicle repair recommendation set, wherein the composite vehicle repair recommendation set identifies the selected recommended vehicle repair operation, and wherein the composite vehicle repair recommendation set does not identify the unselected recommended vehicle repair operation; and providing the composite vehicle repair recommendation set to one or more claims management systems.
Systems and methods are provided for automating the process of generating image metadata related to a vehicle and damage sustained by the vehicle during a collision event by using image analysis tools employing machine learning algorithms. The image with collision metadata renders the image capable of being analyzed using content-based searching.
G06K 9/62 - Methods or arrangements for recognition using electronic means
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
65.
METHODS FOR MANAGING REPAIR OF VEHICLE DAMAGE WITH HEAD MOUNTED DISPLAY DEVICE AND DEVICES THEREOF
Systems and methods are provided for generating repair procedures, which are displayed on a client computing device as a series of repair steps based on a determined order. A user may be directed to capture an image that includes vehicle identifying information or license plate number using a computer wearable device. The damage information, repair estimate information, and repair procedure information may be obtained based on the damaged vehicle information. Individual repair procedures and their order are determined by analyzing the damage information, repair estimate information, repair procedure information, diagnostic codes, and historical repair data. The user may use the system in a handsfree manner by viewing the repair procedures in a display of a computer wearable device which allows the user to view the repair information while performing the repairs. Additionally, the user may use voice commands or gesture to control the display of particular repair procedures.
09 - Scientific and electric apparatus and instruments
Goods & Services
Downloadable computer software and mobile application software for medical bill review, auditing and work flow management; downloadable computer software and mobile application software for medical and health-care cost review and cost management, insurance claims adjusting, and managing insurance claims and settlements; downloadable computer software and mobile application software for insurance claim analysis in the fields of auto casualty, worker's compensation, vehicle repair and vehicle repair estimating; downloadable computer software and mobile application software for the management of vehicle collision and vehicle repair businesses; downloadable computer database featuring automotive repair, diagnostic and estimating information; downloadable software application for employee health screening
16 - Paper, cardboard and goods made from these materials
35 - Advertising and business services
36 - Financial, insurance and real estate services
42 - Scientific, technological and industrial services, research and design
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
Goods & Services
Automobile collision and repair estimating printed manuals Business services, namely, providing business analysis and information regarding the management, processing, and administration of insurance claims; arranging of managed care contractual services in the fields of diagnostic imaging, home health care, durable medical equipment, specialty pharmacy, diagnostic lab services, and healthcare network services; business consulting services in the field of medical invoice review, and providing insurance reimbursement recommendations to others for commercial purposes; medical cost management; health care utilization and review services; health care cost containment; managed care services, namely, electronic processing of health care information, utilization review and pre-certification services, and review of health care claims for appropriate clinical management for business purposes; logistics management services in the field of healthcare, namely, planning and coordinating specialized medical equipment, in-home health care, medical diagnostic services, accessibility specialists and contractors, sub-acute and detoxification, and transportation of people for others in the field of healthcare; medical claims management services, namely, receiving, data entering, and re-pricing of transactions that are originated by physicians, hospitals, and ancillary medical care providers; business networking services, namely, coordinating and facilitating through networks of patient care and goods vendors and providers; administration of pharmacy utilization programs, namely, pharmaceutical cost management and drug utilization review services; provision of business information and business analysis concerning healthcare benefits and pharmacy benefits of individuals and their workers' compensation, automobile insurance and pain management treatment claims; physician referrals; insurance provider and medical provider claims management services, namely, receiving, data entering, and re-pricing of transactions that are originated by insurance providers, physicians, hospitals, and ancillary medical care providers Pharmacy benefit management services; pharmacy and healthcare benefit management consulting services; insurance claims administration; insurance and medical provider claims processing services; insurance services in the nature of loss control management for others; preferred provider network programs, namely, administration of medical benefits provided through a network of health care providers under a workers' compensation insurance plan; providing information regarding workers' compensation insurance policy rates; providing information in the field of workers' compensation Providing temporary use of non-downloadable web-based software applications for use in the management, administration and processing of auto physical damage claims and auto glass replacement claims; providing temporary use of on-line non-downloadable software featuring repair data and procedures for assessing or repairing damaged vehicles; providing temporary use of non-downloadable web-based software applications for use in the management, processing and administration of insurance claims; providing on-line non-downloadable software for identifying, correcting and adjusting billing and coding errors in medical claims Medical assistance services; providing medical, health and wellness information
68.
Systems and methods for determining a provider-specific likelihood of payment acceptance
Embodiments of the application are directed toward a method comprising: receiving, by a transaction management computing apparatus, an electronic payment estimate via a secure communication channel for services rendered by a provider; receiving determining a likelihood of payment acceptance by generating, by the transaction management computing apparatus, an payment amount acceptable to the provider computing device based on data associated with the provider computing device, a type of service provided, or a number of days to make the payment; determining, by the transaction management computing apparatus, whether the generated exact amount is acceptable to the provider computing device; and completing, by the transaction management computing apparatus, a payment transaction with the generated exact amount when the generated exact amount is determined to be acceptable to the provider computing device.
Systems and methods are provided for automating the process of automatically determining appropriateness of surgical team services performed during a medical procedure. Clinical resource data with known surgical guideline indicator (SGIs) may be us used to generate and store a mapping of medical procedure codes to indications of the appropriateness of surgical team services corresponding to the medical procedure codes. A medical bill associated with an insurance claim may be analyzed to extract a medical procedure code corresponding to a surgical procedure, and an automated adjudication recommendation for the medical bill may be made based on the mapping between medical procedure codes and SGIs.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G06Q 20/14 - Payment architectures specially adapted for billing systems
G16H 70/20 - ICT specially adapted for the handling or processing of medical references relating to practices or guidelines
A new automotive collision repair technology is provided, including system and data flow architectures that are designed to provide enhanced data and enhanced data flow in the context of vehicle diagnosis and repair, particularly when repairs are necessary due to collisions. In some examples, the data flow through the network is streamlined, to avoid network congestion, to use fewer computer and network resources and/or to enable the utilization of smaller databases. In other examples, enhanced access to data in real-time and near real-time enabled by a workflow module supports more accurate and timely decisions on vehicle repair. An advantage of this new automotive collision repair technology is that it enables a determination of relatedness likelihood of individual DTC, which in turn decreases costs and increases savings.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
B60R 21/0136 - Electrical circuits for triggering safety arrangements in case of vehicle accidents or impending vehicle accidents including means for detecting collisions, impending collisions or roll-over responsive to actual contact with an obstacle
G06Q 10/20 - Administration of product repair or maintenance
G07C 5/00 - Registering or indicating the working of vehicles
72.
METHODS FOR AUTOMATICALLY PROCESSING VEHICLE COLLISION DAMAGE ESTIMATION AND REPAIR WITH WEARABLE COMPUTING DEVICES
Systems and methods are provided for automatically generating a repair estimate report for repairing a damaged vehicle. A user may be directed to capture data that includes vehicle information (e.g., VIN) and damage information (e.g., images of damaged panels and parts) using a computer wearable device based on intake instructions generated by the system. The damage information may be analyzed to obtain repair information. The repair estimate may be submitted to an insurance carrier and a notification specifying an approval or rejection may be generated. The user may use the system in a handsfree manner by viewing and/or listening to intake instructions, vehicle information, and the status of the repair estimate approval in a display and/or through speakers, respectively, of a computer wearable device.
Disclosed technology includes extracting claimant medical data including a current claimant's age, gender, and at least one injury from an electronic claims document. Estimated injury recovery time data is determined by correlating demographic medical data comprising prior estimated injury recovery time data associated with different prior claimant's ages, genders, and injuries based on programmed estimation rules configured to identify statistical correspondence between different combinations of the ages, the genders, and the injuries in the demographic medical data and the claimant medical data comprising at least the current claimant's age, gender, and at least one injury. The determined estimated injury recovery time data is updated based on at least identified and obtained medical treatment data and prescription medication data associated with the current claimant's at least one injury. The updated estimated injury recovery time data is provided via a graphical user interface to a claim management device.
G06Q 40/00 - Finance; Insurance; Tax strategies; Processing of corporate or income taxes
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
74.
Methods for evaluating and optimizing preferred provider organization (PPO) network stacks and devices thereof
Methods, non-transitory machine readable media, and network stack analysis devices that generate optimized preferred provider organization (PPO) network stacks are disclosed. With this technology, electronic transactions are applied to each of a first plurality of network stacks to determine a cost reduction value for each of the first network stacks. Each of the first network stacks includes an ordered subset of networks. The first network stacks are resampled based on the determined cost reduction values. A determination is made when one or more convergence criteria are met by the resampled first network stacks. When the determination indicates that the convergence criteria are not met by the resampled first network stacks, one or more of the first network stacks are modified based on genetic crossover or mutation operation(s) to generate a second plurality of network stacks. The application, resampling, and determination are then repeated for the second network stacks.
A method, non-transitory computer readable medium, and computing apparatus that identifies with automated image analysis two or more different types of content in image data for an electronic image associated with one or more of a plurality of types of claims. The image data associated with each of the identified two or more different types of content is converted by a different one of a plurality of automated content conversion techniques based on the association with the one or more types of claims and on the identified one of the plurality of types of content. Modified image data for the electronic image is generated based on the converted image data associated with each of the identified two or more different types of content. The modified image data for the electronic image with the converted image data for each of the identified two or more different types of content is provided.
A method, non-transitory computer readable medium, and an apparatus for automated estimation of repair data includes applying a first generated artificial intelligence model on a received vehicle damage image associated with an electronic claim to identify damaged component(s) on a vehicle without using any metadata. A heat map analysis is performed on the received actual vehicle damage image to identify a damage severity value associated with at least one of the identified damaged component(s). A second generated artificial intelligence model is applied on the received actual vehicle damage image and the damage severity value associated with the identified damaged component(s) to determine repair data and a repair-or-replace designation. The determined repair data and the determined repair-or-replace designation for at least one of the identified one or more damaged components is provided in response to the received actual vehicle damage image associated with the electronic claim.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
77.
METHODS FOR ESTIMATING REPAIR DATA UTILIZING ARTIFICIAL INTELLIGENCE AND DEVICES THEREOF
A method, non-transitory computer readable medium, and an apparatus for automated estimation of repair data includes applying a first generated artificial intelligence model on a received vehicle damage image associated with an electronic claim to identify damaged component(s) on a vehicle without using any metadata. A heat map analysis is performed on the received actual vehicle damage image to identify a damage severity value associated with at least one of the identified damaged component(s). A second generated artificial intelligence model is applied on the received actual vehicle damage image and the damage severity value associated with the identified damaged component(s) to determine repair data and a repair-or-replace designation. The determined repair data and the determined repair-or-replace designation for at least one of the identified one or more damaged components is provided in response to the received actual vehicle damage image associated with the electronic claim.
Methods, non-transitory computer readable media, and insurance claim analysis devices are disclosed that provide an improved, automated delta velocity determination. With this technology, one or more images of a damaged motor vehicle and contextual data, associated with an electronic insurance claim and a motor vehicle accident involving the damaged motor vehicle, are obtained. The obtained images and one or more portions of the contextual data are compared to historical sets of images of damaged motor vehicles and corresponding additional contextual data and actual delta velocity values. A delta velocity value is calculated based on the comparison. The calculated delta velocity value is provided to verify damage severity during automated processing of the electronic insurance claim.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G07C 5/00 - Registering or indicating the working of vehicles
G06F 18/214 - Generating training patterns; Bootstrap methods, e.g. bagging or boosting
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
79.
Systems and methods for use of diagnostic scan tool in automotive collision repair
A new automotive collision repair technology is provided, including system and data flow architectures that are designed to provide enhanced data and enhanced data flow in the context of vehicle diagnosis and repair, particularly when repairs are necessary due to collisions. In some examples, the data flow through the network is streamlined, to avoid network congestion, to use fewer computer and network resources and/or to enable the utilization of smaller databases. In other examples, enhanced access to data in real-time and near real-time enabled by a Workflow Module supports more accurate and timely decision on vehicle repair. An advantage of this new automotive collision repair technology is that it enables proper and proven repairs, which in turn increases operation safety of repaired vehicle and people safety.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
A method, non-transitory computer readable medium, and apparatus that automated assessment of conditioning includes automatically analyzing one or more electronic images of a total loss property based on one or more prior condition assessments and condition guidelines rating data associated with the total loss property. A prior property conditioning of the total loss property is determined based on the analysis of the one or more obtained images. The determined prior property conditioning of the total loss property is provided.
Methods, non-transitory computer readable media, and apparatuses for automated processing of hybrid electronic invoice data include identifying at least a first type of charge data from one or more other types of charge data in received hybrid electronic invoice data based on one or more parsing techniques. The first type of charge data is disassembled from the received hybrid electronic invoice data based on the identification. The disassembled first type of charge data is adjudicated based on execution of one of a plurality of sets of adjudication procedures identified to correspond to the disassembled first type of charge data. The received hybrid electronic invoice data is transformed with the adjudicated first type of charge data. The transformed electronic invoice data is provided for additional processing.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G06F 40/117 - Tagging; Marking up ; Designating a block; Setting of attributes
A method, non-transitory computer readable medium and apparatus for providing predictive estimates of repair lines includes receives vehicle damage data including a plurality of images, videos, and vehicle diagnostic data. One or more damages are identified based on the received vehicle damage data. One or more repair parts data and labor data are determined for the identified one or more damages based on historical repair parts data and historical labor data. The determined one or more repair parts data and the labor data is provided via a graphical user interface.
83.
METHODS FOR ANALYZING INSURANCE DATA AND DEVICES THEREOF
Methods, non-transitory computer readable media, and computing apparatus that assist with analyzing data includes obtaining vehicle data from one of the plurality of data sources in a plurality of formats. The obtained vehicle data is aggregated based on one or more geographic locations obtained from one of the plurality of sources. A sampling threshold size is determined for sampling the aggregated vehicle data based on one or more threshold rules. One or more machine learning algorithms are applied to the aggregated vehicle data to generate sampling data when the aggregated vehicle data is greater than the determined sampling threshold size. The generated sampling data is represented in a graphical representation format via a graphical user interface.
Methods and systems for performing the methods are disclosed. The methods include splitting a large execution load/execution component link generation job, into a number of smaller execution load/execution component link generation jobs, and conditionally subsplitting one or more of the smaller execution load/execution component link generation jobs. The methods also include solving each of the smaller execution load/execution component link generation jobs to generate links between data packets corresponding with execution loads of each smaller execution load/execution component link generation job and data packets corresponding with execution components of each smaller execution load/execution component link generation job.
The disclosed systems and methods generate links for candidate execution load/execution component pairings, each candidate pairing identifying one of the data packets corresponding with the execution loads and one of the data packets corresponding with the execution components. Ranks are generated for the candidate pairings, and candidate pairings are selected for potential linkage based on the ranks. If the data packet corresponding with an execution load of a candidate pairing is linkable to the data packet corresponding with an execution component of the candidate pairing, the data packet corresponding with the execution load is linked to the data packet corresponding with the execution component. If the data packet corresponding with the execution load of the candidate pairing is not linkable to the data packet corresponding with the execution component of the pairing, a next candidate pairing is selected.
A new automotive collision repair technology is provided, including system and data flow architectures that are designed to provide enhanced data and enhanced data flow in the context of vehicle diagnosis and repair, particularly when repairs are necessary due to collisions. In some examples, the data flow through the network is streamlined, to avoid network congestion, to use fewer computer and network resources and/or to enable the utilization of smaller databases. In other examples, enhanced access to data in real-time and near real-time enabled by a Workflow Module supports more accurate and timely decision on vehicle repair. An advantage of this new automotive collision repair technology is that it enables proper and proven repairs, which in turn increases operation safety of repaired vehicle and people safety.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
41 - Education, entertainment, sporting and cultural services
Goods & Services
(1) Providing recognition to businesses in the insurance industry that demonstrate excellence in the field of management, processing and administration of insurance claims by way of conducting and hosting incentive award programs and gala events.
(2) On-line publication of electronic newsletters in the field of management, processing and administration of insurance claims; Educational services, namely, conducting conferences, seminars, workshops and classes in the field of management, processing and administration of insurance claims
42 - Scientific, technological and industrial services, research and design
Goods & Services
Providing temporary use of non-downloadable web-based
software applications for use in the management, processing
and administration of insurance claims.
92.
Automatically generating links for data packets in an electronic system
Systems and methods of allocating execution loads to execution components are disclosed. The systems and methods select one of the execution components and one of the execution loads based on selection criteria. The systems and methods then determine whether the selected execution load may be allocated to the selected execution component. If the selected execution load may be allocated to the selected execution component, the systems and methods allocate the execution load accordingly. If the selected execution load may not be allocated to the selected execution component, the systems and methods select another one of the execution components and another one of the execution loads for attempted allocation.
(1) Business services, namely, providing business analysis and information regarding the management, processing, and administration of insurance claims
94.
Methods for vehicle valuation utilizing automated integration of build sheet data and devices thereof
A method, non-transitory computer readable medium and apparatus for vehicle valuation includes integrating with an insurance claim application executed by an agent device in response to an electronic request for a claim for a vehicle. Automated valuation of the claim vehicle in the insurance claim application executed by an agent computing device is managed. Corresponding build sheet data from a build sheet data server device for the comparable vehicles and the vehicle based on a corresponding vehicle identifier for each is obtained. A comparable base value of each of the comparable vehicles to the claim vehicle is adjusted based on differences between the obtained build sheet data for each. A claim base value for the claim vehicle is determined based on the adjusted comparable base values for each of the identified comparable vehicles. The determined claim base value is set in the insurance claim application executed by the agent device.
A method, non-transitory computer readable medium and apparatus for vehicle valuation includes integrating with an insurance claim application executed by an agent device in response to a received electronic request for a claim for a vehicle. Automated valuation of the claim vehicle in the insurance claim application executed by an agent computing device is managed. Corresponding build sheet data from a build sheet data server device for the comparable vehicles and the claim vehicle based on a corresponding vehicle identifier for each is obtained. A comparable base value of each of the comparable vehicles to the claim vehicle is adjusted based on differences between the obtained build sheet data for each. A claim base value for the claim vehicle is determined based on the adjusted comparable base values for each of the identified comparable vehicles. The determined claim base value is set in the insurance claim application executed by the agent device.
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) Providing temporary use of non-downloadable web-based software applications for use in the management, processing and administration of insurance claims.
41 - Education, entertainment, sporting and cultural services
Goods & Services
On-line electronic newsletters in the field of management, processing and administration of automotive and healthcare insurance claims, excluding crop insurance claims; Providing recognition and incentives by the way of awards to demonstrate excellence in the field of management, processing and administration of automotive and healthcare insurance claims, excluding crop insurance claims; Educational services, namely, conducting conferences, seminars, workshops and classes in the field of management, processing and administration of automotive and healthcare insurance claims, excluding crop insurance claims
42 - Scientific, technological and industrial services, research and design
Goods & Services
Providing temporary use of non-downloadable web-based software applications for use in the management, administration and processing of auto physical damage claims and auto glass replacement claims.
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) Providing temporary use of non-downloadable web-based software applications for use in the management, administration and processing of auto physical damage claims and auto glass replacement claims
100.
SYSTEMS AND METHODS FOR USE OF DIAGNOSTIC SCAN TOOL IN AUTOMOTIVE COLLISION REPAIR
A new automotive collision repair technology is provided, including system and data flow architectures that are designed to provide enhanced data and enhanced data flow in the context of vehicle diagnosis and repair, particularly when repairs are necessary due to collisions. In some examples, the data flow through the network is streamlined, to avoid network congestion, to use fewer computer and network resources and/or to enable the utilization of smaller databases. In other examples, enhanced access to data in real-time and near real-time enabled by a Workflow Module supports more accurate and timely decisions on vehicle repair. An advantage of this new automotive collision repair technology is that it enables proper and proven repairs, which in turns increases operation safety of repaired vehicle and people safety.
G06Q 10/20 - Administration of product repair or maintenance
B60S 5/00 - Servicing, maintaining, repairing, or refitting of vehicles
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
