	US 12,462,380 B2
	Method and system for simultaneous classification and regression of clinical data
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); and Qi Song, Seattle, WA (US)
Assigned to SHENZHEN KEYA MEDICAL TECHNOLOGY, Shenzhen (CN)
Filed by SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION, Shenzhen (CN)
Filed on Apr. 20, 2022, as Appl. No. 17/725,051.
Claims priority of provisional application 63/178,923, filed on Apr. 23, 2021.
Prior Publication US 2022/0351374 A1, Nov. 3, 2022
Int. Cl. 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)

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)]

17 Claims

1. A computer-implemented method for analyzing clinical data, comprising:

extracting, by a processor, a first feature information by applying a neural network to a medical image containing a vessel in the clinical data;

predicting, by the processor, a disease status related parameter by applying a regression model to the extracted first feature information;

generating, by the processor, a second feature information based on the extracted first feature information and the disease status related parameter; and

predicting, by the processor, a disease status classification result by applying a classification model to the second feature information;

wherein the disease status related parameter includes an estimation score of a Fractional Flow Reserve (FFR) of the vessel or a plaque vulnerability risk score of the vessel, and the disease status classification result includes a stenosis level or a plaque vulnerability level of the vessel.