Yanfeng Hong, Sisi Zhu, Yuhong Liu, Chao Tian, Hongquan Xu, Gongxing Chen, Lin Tao, Tian Xie. The integration of artificial intelligence into traditional Chinese medicine[J]. Journal of Pharmaceutical Analysis. doi: 10.1016/j.jpha.2024.101157
Citation:
Yanfeng Hong, Sisi Zhu, Yuhong Liu, Chao Tian, Hongquan Xu, Gongxing Chen, Lin Tao, Tian Xie. The integration of artificial intelligence into traditional Chinese medicine[J]. Journal of Pharmaceutical Analysis. doi: 10.1016/j.jpha.2024.101157
Yanfeng Hong, Sisi Zhu, Yuhong Liu, Chao Tian, Hongquan Xu, Gongxing Chen, Lin Tao, Tian Xie. The integration of artificial intelligence into traditional Chinese medicine[J]. Journal of Pharmaceutical Analysis. doi: 10.1016/j.jpha.2024.101157
Citation:
Yanfeng Hong, Sisi Zhu, Yuhong Liu, Chao Tian, Hongquan Xu, Gongxing Chen, Lin Tao, Tian Xie. The integration of artificial intelligence into traditional Chinese medicine[J]. Journal of Pharmaceutical Analysis. doi: 10.1016/j.jpha.2024.101157
1 School of Pharmacy, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, China;
2 Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines;
Engineering Laboratory of Development and Application of Traditional Chinese Medicines;Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, China
Traditional Chinese medicine (TCM) is an ancient medical system distinctive and effective in treating cancer, depression, coronavirus disease 2019 (COVID-19), and other diseases. However, the relatively abstract diagnostic methods of TCM lack objective measurement, and the complex mechanisms of action are difficult to comprehend, which hinders the application and internationalization of TCM. Recently, while breakthroughs have been made in utilizing methods such as network pharmacology and virtual screening for traditional Chinese medicine research, the rise of machine learning (ML) has significantly enhanced their integration with TCM. This article introduces representative methodological cases in quality control, mechanism research, diagnosis, and treatment processes of TCM, revealing the potential applications of ML technology in TCM. Furthermore, the challenges faced by ML in TCM applications are summarized, and future directions are discussed.