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Journal of Traditional Chinese Medicine ›› 2025, Vol. 45 ›› Issue (5): 1152-1163.DOI: 10.19852/j.cnki.jtcm.20250319.001

• Original Articles • Previous Articles     Next Articles

Study on subtyping and Traditional Chinese Medicine treatment of depression based on machine learning and text mining

FAN Mengyue1, YAO Lin1, ZHANG Guoqing2, WANG Ruixue1, CHEN Kexin1, FAN Yujing1, WANG Ziming1, FU Jia1, CHEN Yongjun1(), WANG Taiyi1()   

  1. 1 Innovation Research Institute of Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
    2 Graduate School of Informatics, Kyoto University, Kyoto 6068501, Japan
  • Received:2024-08-03 Accepted:2024-12-22 Online:2025-10-15 Published:2025-03-19
  • Contact: Prof. WANG Taiyi, Innovation Research Institute of Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250355, China. wangtaiyi@sdutcm.edu.cn;
    Prof. CHEN Yongjun, Innovation Research Institute of Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250355, China. chenyongjun@sdutcm.edu.cn, Telephone: +86-18615605032, +86-15002006186
  • Supported by:
    National Key Research and Development Plan: Regulatory Pathways and Mechanisms of Conception and Governor Vessels Surface Stimulation in the Treatment of “Uterus and Brain” Disorders(2022YFC3500405);Taishan Scholar Youth Project of Shandong Province(tsqn202306188);National Natural Science Foundation of China: Epigenetic Regulation of Vascular Neural Unit Function by Vascular Endothelial Histone Deacetylase: a New Antidepressant Application and Mechanism of Huangqi Guizhi Wuwu Decoction(82274128);National Natural Science Foundation of China: Study on the Anti-depression Mechanism of Electroacupuncture based on the Regulation of Biological Clock Gene in Prefrontal Cortex(81973948);Joint Fund of Shandong Provincial Natural Science Foundation: High-Throughput Screening and Key Target Validation of Traditional Chinese Medicine Blood-Activating and Stasis-Resolving Components using a Vascular Microenvironment Simulation Chip(ZR2021LZY020);Student Research Training Program of Shandong University of Traditional Chinese Medicine: the Therapeutic Mechanism of Huangqi Guizhi Wuwu Decoction on Chronic Unpredictable Mild Stress Model Mice Based on the Endothelial Nitric Oxide Synthase-Nitric oxide Pathway Research of Vascular Endothelial Eells(202210441008)

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Abstract:

OBJECTIVE: To research the subtyping and treatment of depression by leveraging studying on extensive Traditional Chinese Medicine (TCM) experiences through artificial intelligence (AI).

METHODS: We retrieved depression-related literature published from inception to April 2023 from databases. From these sources, we extracted symptoms, signs, and prescriptions associated with depression. By utilizing the tree number system in the medical subject headings (MeSH), we established a hierarchical relationship matrix for symptoms/signs, as well as depression sample fingerprints. Using an unsupervised clustering algorithm, we constructed a machine learning model for classifying depression patients. Furthermore, we conducted an analysis of medication rules for each depression cluster.

RESULTS: We created a My Structured Query Language (MySQL) database containing datasets of depression-symptoms/signs and depression-herbs, through mining 3522 published clinical literatures on TCM diagnosis and treatment for depression. We established hierarchical relationships among symptoms/signs of depression patients. Our unsupervised clustering analysis revealed that depression patients could be classified into 9 subtypes, with each subtype corresponding to a specific treatment prescription. Notably, one of the depression subtypes was consistently treated by Qi-tonifying formulas and herbs. This finding was further supported by data from Qi-deficiency patients, as there was a high similarity in the top symptoms/signs shared between this subtype and Qi-deficiency diagnosed by TCM.

CONCLUSIONS: This study identified the subtypes and TCM treatment of depression by using machine learning and text mining.

Key words: machine learning, depression, artificial intelligence, medicine, Chinese traditional, disease subtyping

Cite this article

FAN Mengyue, YAO Lin, ZHANG Guoqing, WANG Ruixue, CHEN Kexin, FAN Yujing, WANG Ziming, FU Jia, CHEN Yongjun, WANG Taiyi. Study on subtyping and Traditional Chinese Medicine treatment of depression based on machine learning and text mining[J]. Journal of Traditional Chinese Medicine, 2025, 45(5): 1152-1163.