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:
Mar. 24, 2026

Filed:

Jun. 16, 2020
Applicant:

The Trustees of Princeton University, Princeton, NJ (US);

Inventors:

Hongxu Yin, Princeton, NJ (US);

Bilal Mukadam, Plano, TX (US);

Xiaoliang Dai, Princeton, NJ (US);

Niraj K. Jha, Princeton, NJ (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/00 (2006.01); A61B 5/0205 (2006.01); G06N 3/045 (2023.01); G06N 3/082 (2023.01);
U.S. Cl.
CPC ...
A61B 5/7264 (2013.01); A61B 5/02055 (2013.01); A61B 5/681 (2013.01); A61B 5/7271 (2013.01); G06N 3/045 (2023.01); G06N 3/082 (2013.01);
Abstract

According to various embodiments, a machine-learning based system for diabetes analysis is disclosed. The system includes one or more processors configured to interact with a plurality of wearable medical sensors (WMSs). The processors are configured to receive physiological data from the WMSs and demographic data from a user interface. The processors are further configured to train at least one neural network based on a grow-and-prune paradigm to generate at least one diabetes inference model. The neural network grows at least one of connections and neurons based on gradient information and prunes away at least one of connections and neurons based on magnitude information. The processors are also configured to output a diabetes-based decision by inputting the received physiological data and demographic data into the generated diabetes inference model.


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