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:
Nov. 04, 2025

Filed:

Apr. 20, 2022
Applicant:

Shenzhen Keya Medical Technology Corporation, Shenzhen, CN;

Inventors:

Xin Wang, Seattle, WA (US);

Youbing Yin, Kenmore, WA (US);

Bin Kong, Charlotte, NC (US);

Yi Lu, Seattle, WA (US);

Xinyu Guo, Redmond, WA (US);

Hao-Yu Yang, Seattle, WA (US);

Qi Song, Seattle, WA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06V 10/40 (2022.01); G06V 10/764 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); A61B 6/50 (2024.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G06V 10/40 (2022.01); G06V 10/764 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); A61B 6/504 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30101 (2013.01); G06V 2201/03 (2022.01);
Abstract

This disclosure discloses a method for analyzing clinical data. The Method includes extracting a first feature information by applying a neural network to the clinical data; predicting a disease status related parameter by applying a regression model to the extracted first feature information; generating a second feature information based on the extracted first feature information and the disease status related parameter; and predicting a disease status classification result by applying a classification model to the second feature information. The method can improve the prediction accuracy and the diagnosis efficiency of doctors.


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