10 results about "Electronic submission" patented technology

Aspects of the present disclosure relate to automated evaluation of electronic datasets. Embodiments include receiving one or more rules related to evaluation of electronic datasets. Embodiments further include generating, via an embedding model, embedding representations of the one or more rules. Embodiments further include receiving an electronic dataset. Embodiments further include identifying a rule that is applicable to the electronic dataset based on using a machine learning model configured to search the embedding representations of the one or more rules based on the electronic dataset. Embodiments further include evaluating, using the machine learning model or an additional machine learning model, the electronic dataset based on the identified rule. Embodiments further include using the machine learning model or the additional machine learning model to generate an evaluation summary for the electronic dataset based on determining that an item within the electronic dataset does not comply with the identified rule.

A computer implemented platform coordinates student participation in clinical shadowing and volunteering. An application server communicates with user devices to authenticate student and professional accounts, display filtered opportunity listings, and record attendance with timestamp and geolocation captured from a student device. The platform generates a session identifier, binds the captured fields to the identifier, and transmits a validation request to a verified professional or organization leader. Upon receiving validation, the system persists a tamper resistant log entry, updates cumulative progress against program specific hour goals, and triggers reminders generated by a requirements engine. Interfaces allow in app messaging for scheduling and confirmation. An export module formats validated histories for direct electronic submission to application portals or for download, enabling end to end discovery, recording, verification, tracking, and export.

Disclosed is a system and / or a method for near-instant utility patent allowance and rejection via AI-powered legal reasoning. A computer-implemented method for near-instant evaluation of a utility patent application for an allowance and a rejection. The method includes receiving, by an artificial intelligence (AI) engine, an electronic submission of the utility patent application including at least one claim, a specification, one or more figures, and / or any associated oath and declaration.

Some embodiments provide systems and methods for gas pipeline pathway analysis, control and communication. In some embodiments, a physical pipeline scheduling and control system comprises a server or computer-based computing system configured to receive a user input corresponding to a request for a gaseous resource, automatically obtain data from a plurality of data sources, automatically simulate a plurality of potential pathways of the gas pipeline network, automatically output a pathway recommendation comprising at least a first recommended pathway, receive a user selection of a selected recommended pathway, automatically format a nomination for the selected recommended pathway, and automatically access and control a separate electronic submission system and electronically submit the nomination for the request for the gaseous resource to the electronic submission system for execution.

Systems, methods, and computer-readable media are disclosed for processing electronic transactions. In some embodiments, a server computing device may combine parameters of electronic documents expressing multiple patient encounters in a single encounter group; and initiate a call to an application programming interface (API) for creation of one or more electronic documents expressing one or more claims for electronic submission to one or more paying parties based, at least in part, on the combined parameters.

According to an embodiment of the present invention, a computer system comprises a processor set, one or more computer-readable storage media, and program instructions stored on the one or more computer-readable storage media to cause the processor set to perform operations. The system analyzes a document to obtain parameters including an area of research in the document and metrics for quality of the document. A document influence score of the document is determined based on the parameters. An author influence score is determined based on a quantity of citations to an author of the document. An entity is selected for submission of the document based on the document influence score and the author influence score. The document is electronically submitted to the selected entity. Embodiments of the present invention further include a method and computer program product for electronically submitting a document in substantially the same manner described above.

Aspects of the present disclosure describe a system comprising a computer-readable storage medium storing a program and method for analyzing one or more electronic submissions based on a rule set to generate a risk assessment of an applicant. In particular, some embodiments analyze one or more electronic submissions for an applicant of an insurance policy (or insurance product) based on a rule set (e.g., structured, machine-readable rule set) that describes one or more rules, guidelines, or parameters that codify an insurance carrier's risk appetite. Based on the analysis, various embodiments generate a risk assessment for the applicant, where the risk assessment can include a risk summary, a risk classification, a risk score, a listing of detected risk signals, or some combination thereof for the applicant.

Systems, methods, and devices for managing and processing electronic documents by extracting semantic information, generating high-dimensional embeddings, and automating form completion through advanced natural language processing (NLP) models and optimized similarity algorithms may include receive a plurality of electronic files associated with an electronic Submission Template and Resource (eSTAR) form. Semantic information may be extracted from the plurality of electronic files using a pre-trained natural language processing (NLP) model. The electronic files may be segmented into content slices based on the extracted semantic information. The content slices and the corresponding high-dimensional embeddings may be stored in a vector database. An indication of one or more sections of the eSTAR form may be received. The indication of the one or more sections of the eSTAR form may be converted into one or more query embeddings. A set of content slices of the plurality of content slices may be determined and transmitted.

Aspects of the present disclosure describe a system comprising a computer-readable storage medium storing a program and method for analyzing one or more electronic submissions based on a rule set to generate a risk assessment of an applicant. In particular, some embodiments analyze one or more electronic submissions for an applicant of an insurance policy (or insurance product) based on a rule set (e.g., structured, machine-readable rule set) that describes one or more rules, guidelines, or parameters that codify an insurance carrier's risk appetite. Based on the analysis, various embodiments generate a risk assessment for the applicant, where the risk assessment can include a risk summary, a risk classification, a risk score, a listing of detected risk signals, or some combination thereof for the applicant.

Systems, methods, and devices for managing and processing electronic documents by extracting semantic information, generating high-dimensional embeddings, and automating form completion through advanced natural language processing (NLP) models and optimized similarity algorithms may include receive a plurality of electronic files associated with an electronic Submission Template and Resource (eSTAR) form. Semantic information may be extracted from the plurality of electronic files using a pre-trained natural language processing (NLP) model. The electronic files may be segmented into content slices based on the extracted semantic information. The content slices and the corresponding high-dimensional embeddings may be stored in a vector database. An indication of one or more sections of the eSTAR form may be received. The indication of the one or more sections of the eSTAR form may be converted into one or more query embeddings. A set of content slices of the plurality of content slices may be determined and transmitted.