Systems Theory-Driven Framework for AI Integration into the Holistic Material Basis Research of Traditional Chinese Medicine

2024, Volume 38, Issue 7

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Engineering doi: 10.1016/j.eng.2024.04.009

Systems Theory-Driven Framework for AI Integration into the Holistic Material Basis Research of Traditional Chinese Medicine

^aSchool of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, China
^bState Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China

Received: 2024-01-20 Revised: 2024-04-14 Accepted: 2024-04-16 Available online: 2024-04-26

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Abstract

This research introduces a systems theory-driven framework to integration artificial intelligence (AI) into traditional Chinese medicine (TCM) research, enhancing the understanding of TCM’s holistic material basis while adhering to evidence-based principles. Utilizing the System Function Decoding Model (SFDM), the research progresses through define, quantify, infer, and validate phases to systematically explore TCM’s material basis. It employs a dual analytical approach that combines top-down, systems theory-guided perspectives with bottom-up, elements–structure–function methodologies, provides comprehensive insights into TCM’s holistic material basis. Moreover, the research examines AI’s role in quantitative assessment and predictive analysis of TCM’s material components, proposing two specific AI-driven technical applications. This interdisciplinary effort underscores AI’s potential to enhance our understanding of TCM’s holistic material basis and establishes a foundation for future research at the intersection of traditional wisdom and modern technology.

Keywords

Artificial intelligence ; Systems theory ; Traditional Chinese medicine ; Material basis ; Bottom-up

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