Machine learning prediction of myocardial ischaemia‒reperfusion injury: Clinical features and Qishen Yiqi dripping pills mechanism

Teng Ge

doi:10.1016/j.phymed.2025.157590

Machine learning prediction of myocardial ischaemia‒reperfusion injury: Clinical features and Qishen Yiqi dripping pills mechanism

2025-11-24

0

PRE

AI

T

Teng Ge

R

Rongjun Zou

J

Jingyu Bo

L

Liangbin Yang

J

Jinlin Hu

B

Bo Ning

Y

Yingwen Li

Z

Zong-Qi Pan

P

Pengtao Sun

S

Sinan Chen

J

Jing Ju

张

张苗 (Miao Zhang)

K

Kunyang He

G

Guanmou Li

C

Chaojie Wang

J

Jihai Peng *

Y

Yang Zhi-min *

X

Xiaoping Fan *

DOI：10.1016/j.phymed.2025.157590

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Abstract

En 中文

Myocardial ischaemia‒reperfusion injury (MIRI) is a common complication following cardiopulmonary bypass (CPB) surgery. Most existing studies focus on basic research, with limited exploration of clinical patterns. The aim of this study was to analyse the key factors influencing postoperative mortality in MIRI patients, incorporate traditional Chinese medicine (TCM) classifications to reflect overall patient status, construct an optimal machine learning model for precise prognosis assessment, and investigate the intervention mechanism of Qishen Yiqi dripping pills (QSYQ).

Machine learning prediction of myocardial ischaemia‒reperfusion injury: Clinical features and Qishen Yiqi dripping pills mechanism

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