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:
Sep. 30, 2025

Filed:

Dec. 21, 2021
Applicant:

Uipco, Llc, San Antonio, TX (US);

Inventors:

Nolan Serrao, Plano, TX (US);

Keegan Patrick Hayes, Whitestown, IN (US);

Arthur Quentin Smith, Fredericksburg, TX (US);

John Andrew Weems, San Antonio, TX (US);

Salvador Adrian Bretado, San Antonio, TX (US);

Justin Royell Nash, Little Elm, TX (US);

David Joaquin Harris, San Antonio, TX (US);

Carol Lyn Lawrence, Fair Oaks Ranch, TX (US);

Theresa Marie Matowitz, San Antonio, TX (US);

Courtney St. Martin, Duluth, GA (US);

Assignee:
Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G16H 20/70 (2018.01); G06F 9/451 (2018.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
G16H 20/70 (2018.01); G06F 9/453 (2018.02); G16H 50/20 (2018.01);
Abstract

Aspects of the present disclosure are directed to a cognition analysis and response system that can A) identify and classify machine learning training data and use the training data to build a cognitive impairment machine learning model; B) identify cognitive impairments by applying the cognitive impairment machine learning model and performing a false positive/false negative analysis; and C) apply various automated adaptive measures for users with identified cognitive impairment. The cognition analysis and response system can generate training data by using an unsupervised training process and verifying results with validations of training items that have been pre-classified. The cognition analysis and response system can then iterate through each set of inputs paired with cognitive impairment classification, applying a machine learning model and updating the model based on a comparison of the model output to the cognitive impairment classification.


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