The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 02, 2025

Filed:

Jul. 15, 2024
Applicant:

Nayya Health, Inc., New York, NY (US);

Inventors:

Sina Chehrazi, New York, NY (US);

John Joseph Glorioso, Jr., Laurel, MD (US);

Akash Magoon, New York, NY (US);

Aman Magoon, Fallston, MD (US);

Assignee:

Nayya Health, Inc., New York, NY (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 40/08 (2012.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01); G06Q 10/10 (2023.01); G16H 10/60 (2018.01); G16H 40/20 (2018.01); G16H 50/20 (2018.01); G16H 20/10 (2018.01);
U.S. Cl.
CPC ...
G06Q 40/08 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06Q 10/10 (2013.01); G16H 10/60 (2018.01); G16H 40/20 (2018.01); G16H 50/20 (2018.01); G16H 20/10 (2018.01);
Abstract

A data processing system for insurance claims analysis and adjudication implements obtaining policy coverage information for each of a plurality of insurance policies and insurance claim information associated with a plurality of insurance claims associated with an insured user, analyzing the insurance claim information using a first machine learning to obtain event-related claim grouping information; analyzing the event-related claim grouping information and the standardized policy information using the second machine learning model to obtain coverage prediction information comprising a prediction, for each event of the one or more events, identifying a respective insurance policy of the plurality of insurance policies likely to cover the one or more claims associated with each event, the second machine learning model being trained using second training data formatted according to the standard schema; and providing, via a network connection, the coverage prediction information to a computing device associated with the insured user.


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