Discussion on Construction of a Multi-Agent "Cross-scale" Collective Decision-making Model for Superior Disease Entities in Sichuan-style Traditional Chinese Medicine
10.13422/j.cnki.syfjx.20251512
- VernacularTitle:川派中医优势病种的多智能体“跨维度”群决策模型构建探讨
- Author:
Qiuping CHEN
1
;
Hang ZHOU
2
;
Dan ZHENG
3
;
Baixue LI
2
;
Chenhao LIU
1
;
Ju CHEN
4
;
Jibin LIU
2
;
Quansheng FENG
1
;
JIANGYUMING
5
;
Cen JIANG
1
Author Information
1. Academic Inheritance Center of Traditional Chinese Medicine（TCM）， Chengdu University of TCM， Chengdu 610075，China
2. Basic Medical College， Chengdu University of TCM， Chengdu 611137，China
3. Clinical Medical College/Affiliated Hospital， Chengdu University of TCM， Chengdu 610075，China
4. Intelligent Medical College， Chengdu University of TCM， Chengdu 611137，China
5. Digital Key Laboratory of Unearthed Medical Literature and Cultural Relics Protection， Chengdu University of TCM， Chengdu 611137，China
- Publication Type:Journal Article
- Keywords:
academic schools;
dominant diseases;
multimodal;
generative artificial intelligence;
intelligent agent;
group decision-making
- From:
Chinese Journal of Experimental Traditional Medical Formulae
2026;32(14):1-13
- CountryChina
- Language:Chinese
-
Abstract:
At present， the systematic excavation of the clinical experience and academic thought of the Sichuan school of Chinese medicine vis-à-vis its dominant disease entities remains fragmentary， and replicable paradigms are scarce. Confronted with empirical fragmentation， data heterogeneity and decision-making subjectivity， the standardised distillation， inheritance and clinical translation of these distinctive experiences has become a critical bottleneck constraining the development of the Sichuan school. The integration of artificial-intelligence technologies in data processing， pattern recognition and intelligent decision-making has rendered deep mining of traditional Chinese medicine（TCM） clinical knowledge and patterns imperative. Constructing an intelligent modern TCM diagnostic-therapeutic-evaluative system is now the obligatory route for inheritance and innovation in Chinese medicine， and simultaneously provides a technological breakthrough for intelligent decision paradigms in the dominant diseases of the Sichuan school. Accordingly， this study adopts the regional academic school as its point of entry， focuses on the dominant diseases of the Sichuan school， and proposes an innovative pathway of "four-dimensional data-multi-modal fusion-multi-agent decision-making". Specifically， four data dimensions are defined and instantiated： （Ⅰ） knowledge from classical medical literature and historical case records. （Ⅱ） objective four-diagnosis phenotypic data. （Ⅲ） master physicians' prescribing regularities. （Ⅳ） characteristic mechanisms of renowned formulae. Leveraging multi-modal data fusion and generative artificial intelligence， the entire causal chain of Famous Physicians and Renowned Formulas is explicated to reconstruct the diagnostic-therapeutic cognitive logic of the regional school. Finally， a multi-agent collective-decision model is established and refined for the dominant diseases of the Sichuan school， capable of generating precise， individualised treatment regimens and thereby advancing an intelligent diagnostic-therapeutic paradigm that delivers more efficient and accurate clinical decision support.
