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:
Oct. 07, 2025

Filed:

Mar. 31, 2023
Applicant:

Zhejiang Lab, Hangzhou, CN;

Inventors:

Yu Zhang, Hangzhou, CN;

Jun Li, Hangzhou, CN;

Chaoliang Sun, Hangzhou, CN;

Huan Zhang, Hangzhou, CN;

Zhichao Wang, Hangzhou, CN;

Jingsong Li, Hangzhou, CN;

Assignee:

ZHEJIANG LAB, Hangzhou, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16H 50/30 (2018.01); G06F 17/16 (2006.01); G06T 7/00 (2017.01); G06V 10/62 (2022.01);
U.S. Cl.
CPC ...
G16H 50/30 (2018.01); G06F 17/16 (2013.01); G06T 7/0012 (2013.01); G06V 10/62 (2022.01); G06T 2207/10088 (2013.01); G06T 2207/30016 (2013.01);
Abstract

Disclosed are a disease prediction method, system and apparatus based on a multi-relation functional connectivity matrix. A Pearson correlation coefficient matrix and a DTW distance matrix are respectively calculated according to resting state functional magnetic resonance time series extracted from a brain atlas, the DTW distance matrix is converted in combination with the Pearson correlation coefficient matrix into a DTW' matrix which includes correlation degree and correlation direction information and whose numerical range is equivalent to the value range of a Pearson coefficient, and a functional connectivity matrix is obtained after weighted combination. The present disclosure combines DTW distance information to weaken the dynamic change of functional connectivity and the influence of asynchrony of functional signals in different brain regions on the functional connectivity matrix, so that the calculated functional connectivity matrix can better reflect the correlation between the functional signals in different brain regions.


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