Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Systems, non-transitory machine-readable storage media, and computer-implemented methods are provided for automated scheduling of vehicle repair reinspections.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.