Citation

Huang, Xian and Goh, Hui Hwang and He, Ting Ting and Zhang, Dong Dong and Dai, Wei and Kurniawan, Tonni Agustiono and Goh, Kai Chen and Wong, Hin Yong and Islam, Mohammad Tariqul and Liang, Xue (2026) Integration of traditional Chinese medicine and machine learning: Opportunities, obstacles, and implications for future of healthcare. Journal of Integrative Medicine. ISSN 2095-4964

Text Integration of traditional Chinese medicine and machine learning_ Opportunities, obstacles, and implications for future of healthcare - ScienceDirect.pdf - Published Version Restricted to Repository staff only Download (276kB)

Abstract

Chinese herbal traditions, with a history of over 2000 years, emphasise the harmony between spirit, body and nature. Integrating these principles with machine learning (ML) offers transformative potential for traditional Chinese medicine (TCM). By leveraging technologies and data-driven models, TCM can evolve while preserving its accumulated wisdom. Knowledge graphs combined with deep learning can enhance diagnosis, treatment planning and prognosis evaluation. This paper reviews current ML applications in TCM and strategies for integration with conventional practices. It categorises key challenges and proposed solutions, focusing on deep learning-based algorithms. ML has demonstrated success in automating personalised herbal prescriptions, predicting diagnostic outcomes and identifying acupoints. However, major obstacles include data standardisation, ethical and legal frameworks, and fostering interdisciplinary collaboration. The development of high-quality, ethical artificial intelligence requires regulatory support and cooperation with TCM practitioners. This study supports the notion that a learning platform is essential for the education of TCM practitioners. ML and TCM may adopt this implementation approach, and the emergence of convex ML can substantially enhance testing algorithms in TCM, hence improving the effectiveness of future healthcare systems.

Item Type:	Article
Uncontrolled Keywords:	Chinese medicine, machine learning
Subjects:	R Medicine > R Medicine (General) > R855-855.5 Medical technology
Divisions:	Faculty of Artificial Intelligence & Engineering (FAIE)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	02 Apr 2026 06:41
Last Modified:	06 Apr 2026 06:12
URII:	http://shdl.mmu.edu.my/id/eprint/15663

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