Framework and Implementation Pathway for an Intelligent Decision-Support System Integrating Traditional Chinese and Western Medicine for Coronary Heart Disease
10.13288/j.11-2166/r.2026.22.005
- VernacularTitle:冠心病中西医结合智能辅助诊疗系统的构建框架与实施路径
- Author:
Wenjun WU
1
;
Xinlu WANG
1
;
Rui YU
1
;
Yizhuo LI
1
;
Jingjing WEI
1
;
Bin LI
1
;
Yulong XU
2
;
Mingjun ZHU
1
Author Information
1. Heart Center，The First Affiliated Hospital of Henan University of Chinese Medicine，Zhengzhou，450000
2. School of Information Technology，Henan University of Chinese Medicine
- Publication Type:Journal Article
- Keywords:
coronary heart disease;
integrated traditional Chinese and western medicine;
artificial intelligence;
knowledge graph;
clinical decision support system
- From:
Journal of Traditional Chinese Medicine
2026;67(22):2386-2396
- CountryChina
- Language:Chinese
-
Abstract:
Addressing the insufficient coordination among diagnostic classification， risk stratification， traditional Chinese medicine （TCM） syndrome differentiation， treatment recommendation， and follow-up management of coronary heart disease （CHD） with integrated traditional Chinese and western medicine， this paper proposes a framework and implementation pathway for an intelligent decision-support system integrating traditional Chinese and western medicine for CHD. Based on domestic and international diagnosis and treatment guidelines， TCM clinical practice guidelines， expert consensus statements， and relevant evidence-based evidence of CHD， the integrated diagnostic and treatment pathway for CHD was reconstructed， developing a systematic design framework incorporating western medicine-based diagnostic gating， TCM syndrome element identification and candidate syndrome generation， an integrated traditional Chinese and western medicine knowledge graph， a guideline-based rule engine， model development， and a human-machine collaborative confirmation mechanism. A data framework centered on disease-syndrome-symptom-diagnosis-treatment-rehabilitation-outcome has been established， and an intelligent decision-support workflow has been proposed， comprising "guideline-based rule gating-syndrome element identification and candidate syndrome generation-knowledge graph reasoning-personalized recommendation-physician confirmation-follow-up feedback". In addition， pathways for interpretability， safety， clinical usability， and phased validation are defined to provide a methodological basis for the subsequent development， clinical validation， and regional implementation of intelligent decision-support systems.
