结合医学学报（英文版）2026，Vol.24Issue(1)：98-104,7.DOI:10.1016/j.joim.2025.11.003
Predicting traditional Chinese medicine constitutions in adults aged ≥ 65 years:A machine learning approach
Predicting traditional Chinese medicine constitutions in adults aged ≥ 65 years:A machine learning approach
Chen Sun 1Xiang-long Xu 2Zhen Yu 3Zong-yuan Ge 3Wen-jun Wang 4Bi-ying Wang 5Hua-ling Song 1Guo-qun Xie 1Hai-lei Zhao 1Yang Zhang6
作者信息
- 1. School of Public Health,Shanghai University of Traditional Chinese Medicine,Shanghai 201203,China
- 2. School of Public Health,Shanghai University of Traditional Chinese Medicine,Shanghai 201203,China||School of Translational Medicine,Faculty of Medicine,Nursing and Health Sciences,Monash University,Melbourne 3800,Victoria,Australia||Artificial Intelligence and Modelling in Epidemiology Program,Melbourne Sexual Health Center,Alfred Health,Melbourne 3053,Victoria,Australia||Bijie Municipal Center for Disease Control and Prevention,Bijie 551700,Guizhou Province,China||Bijie Institute of Shanghai University of Traditional Chinese Medicine,Bijie 551700,Guizhou Province,China
- 3. Monash e-Research Center,Faculty of Engineering,Monash University,Melbourne 3800,Victoria,Australia
- 4. Central Clinical School,Faculty of Medicine,Nursing and Health Sciences,Monash University,Melbourne 3800,Victoria,Australia
- 5. School of Public Health,Shanghai University of Traditional Chinese Medicine,Shanghai 201203,China||Three Gorges University Hospital of Traditional Chinese Medicine & Yichang Hospital of Traditional Chinese Medicine,Yichang 443000,Hubei Province,China
- 6. Yu Garden Community Health Care Center,Shanghai 200010,China
- 折叠
摘要
关键词
Traditional Chinese medicine constitution/Aged/Machine learningKey words
Traditional Chinese medicine constitution/Aged/Machine learning引用本文复制引用
Chen Sun,Xiang-long Xu,Zhen Yu,Zong-yuan Ge,Wen-jun Wang,Bi-ying Wang,Hua-ling Song,Guo-qun Xie,Hai-lei Zhao,Yang Zhang..Predicting traditional Chinese medicine constitutions in adults aged ≥ 65 years:A machine learning approach[J].结合医学学报（英文版）,2026,24(1):98-104,7.基金项目
This work was supported by the National Key R&D Program of China(2025YFC3507503),the Traditional Chinese Medicine Research Project of Shanghai Municipal Health Commission(20240N108),and the project on artificial intelligence-driven reform of scientific research paradigms to empower disciplinary advancement. （2025YFC3507503）
