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. 19, 2023

Filed:

Dec. 04, 2019
Applicants:

Acer Incorporated, New Taipei, TW;

National Yang-ming University, Taipei, TW;

Inventors:

Chun-Hsien Li, New Taipei, TW;

Tsung-Hsien Tsai, New Taipei, TW;

Liang-Kung Chen, Taipei, TW;

Chen-Huan Chen, Taipei, TW;

Hao-Min Cheng, Taipei, TW;

Assignees:

Acer Incorporated, New Taipei, TW;

National Yang-Ming University, Taipei, TW;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/00 (2006.01); G16H 50/20 (2018.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01); A61B 5/021 (2006.01); G16H 50/30 (2018.01);
U.S. Cl.
CPC ...
A61B 5/7275 (2013.01); A61B 5/7246 (2013.01); A61B 5/7267 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); A61B 5/021 (2013.01);
Abstract

A feature identifying method and an electronic device are provided. The method includes: obtaining a plurality of physiological information obtained by measuring a subject at a plurality of time points in one day; converting the plurality of physiological information into a plurality of correlation features respectively; establishing a plurality of first risk prediction models according to the plurality of correlation features, and identifying at least one first correlation feature from the plurality of correlation features according to the plurality of first risk prediction models; establishing a plurality of second risk prediction models according to the at least one first correlation feature, and identifying, according to the plurality of second risk prediction models, at least one second correlation feature capable of predicting a specific disease from the at least one first correlation feature; and outputting the at least one second correlation feature.


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