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:
Apr. 04, 2023

Filed:

Feb. 25, 2022
Applicant:

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

Inventors:

Ishan Babbar, New York, NY (US);

Satvik Gadamsetty, North Brunswick, NJ (US);

Bradley Verdino, Long Island City, NY (US);

David Feldman, New York, NY (US);

Daniel Young, New York, NY (US);

Mark Farnum, New York, NY (US);

Akash Magoon, New York, NY (US);

Aman Magoon, New York, NY (US);

Assignee:

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

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 10/10 (2012.01); G06Q 10/06 (2012.01); G06Q 30/02 (2012.01); G06Q 30/06 (2012.01); G06Q 40/08 (2012.01); G06N 20/20 (2019.01); G06Q 10/1057 (2023.01);
U.S. Cl.
CPC ...
G06Q 40/08 (2013.01); G06N 20/20 (2019.01); G06Q 10/1057 (2013.01);
Abstract

A data processing system for machine-learning driven data analysis and reminders implements obtaining insurance claim information associated with a plurality of insurance claims associated with a user, user demographic information for the user or both and obtaining digital healthcare service provider information associated with one or more digital healthcare service providers. The system further implements analyzing the insurance claim information and the user demographic information using a first machine learning model to obtain claim categorization information identifying a types of insurance claims that the user has filed or is likely to file, and analyzing the digital healthcare service provider and the claim categorization information to predict digital health services that the user may benefit from based on the claim categorization information and categories of digital health services included in the digital healthcare service provider information, and providing the digital healthcare service recommendations to a computing device associated with the user.


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