The art of medical synthesis: Where Chinese medical wisdom intersects with artificial intelligence

Lim, ECN; Cheng, NCL; Lim, CED

The art of medical synthesis: Where Chinese medical wisdom intersects with artificial intelligence

Lim, ECN Cheng, NCL Lim, CED

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Journal of Traditional Chinese Medical Sciences, 2025
Issue Date:: 2025-01-01

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Field	Value	Language
dc.contributor.author	Lim, ECN
dc.contributor.author	Cheng, NCL
dc.contributor.author	Lim, CED
dc.date.accessioned	2026-01-13T23:17:19Z
dc.date.available	2026-01-13T23:17:19Z
dc.date.issued	2025-01-01
dc.identifier.citation	Journal of Traditional Chinese Medical Sciences, 2025
dc.identifier.issn	2095-7548
dc.identifier.issn	2095-7548
dc.identifier.uri	http://hdl.handle.net/10453/191754
dc.description.abstract	Generative artificial intelligence (AI), specifically large language models, such as DeepSeek, has accelerated the digital transformation of healthcare systems in both developing and developed countries. The use of AI in diagnostics, image processing and interpretation, treatment personalization, clinical documentation, and drug discovery is an example of the implementation of AI in Western medicine. The need for evidence-based studies and a standardized approach to scientific medicine aligns well with these applications. AI can leave a lasting impact on the Chinese medicine (CM) landscape by increasing expectations and presenting new challenges. The analogy between the CM-specific diagnostic methods and syndrome differentiation, which is holistic, pattern-oriented, patient-centered, and clinical data analysis, is significant at multiple levels. These qualities pose challenges for AI usage in CM, which heavily relies on structured data and pattern recognition. Despite these adversities, AI can still be used in CM through data standardization, prediction formulation, and treatment planning, provided that the integration of this tool considers the primary principles of CM and adheres to ethical and regulatory considerations. This review examines the dichotomous approach to health and medicine in the contexts of AI and CM, highlighting the evolving potential, inherent limitations, and ethical and regulatory issues associated with the application of AI to CM. It provides a foundation for developing technologically progressive yet culturally and philosophically sensitive strategies that are in harmony with traditional clinical values.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Journal of Traditional Chinese Medical Sciences
dc.relation.isbasedon	10.1016/j.jtcms.2025.08.001
dc.rights	info:eu-repo/semantics/openAccess
dc.title	The art of medical synthesis: Where Chinese medical wisdom intersects with artificial intelligence
dc.type	Journal Article
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Science
pubs.organisational-group	University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.date.updated	2026-01-13T23:17:17Z
pubs.publication-status	Published

Abstract:

Generative artificial intelligence (AI), specifically large language models, such as DeepSeek, has accelerated the digital transformation of healthcare systems in both developing and developed countries. The use of AI in diagnostics, image processing and interpretation, treatment personalization, clinical documentation, and drug discovery is an example of the implementation of AI in Western medicine. The need for evidence-based studies and a standardized approach to scientific medicine aligns well with these applications. AI can leave a lasting impact on the Chinese medicine (CM) landscape by increasing expectations and presenting new challenges. The analogy between the CM-specific diagnostic methods and syndrome differentiation, which is holistic, pattern-oriented, patient-centered, and clinical data analysis, is significant at multiple levels. These qualities pose challenges for AI usage in CM, which heavily relies on structured data and pattern recognition. Despite these adversities, AI can still be used in CM through data standardization, prediction formulation, and treatment planning, provided that the integration of this tool considers the primary principles of CM and adheres to ethical and regulatory considerations. This review examines the dichotomous approach to health and medicine in the contexts of AI and CM, highlighting the evolving potential, inherent limitations, and ethical and regulatory issues associated with the application of AI to CM. It provides a foundation for developing technologically progressive yet culturally and philosophically sensitive strategies that are in harmony with traditional clinical values.

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http://hdl.handle.net/10453/191754