Progress in the application of AI in the standardization of traditional Chinese medicine: A review based on machine learning and deep learning
Xianglong Meng, Xiaofen Li, Yuting Li, Zhulin Bu, Yuhui Wu, Shuosheng Zhang
- 发表年份
- 2025
- 引用次数
- 10
摘要
• The application of AI within TCM is discussed • The analysis spans six pivotal domains using ML and DL • This study helps in a path towards an integrated and resilient healthcare future Abstract The Fourth Industrial Revolution, propelled by advancements in the internet, big data, robotics, and artificial intelligence (AI), has not only accelerated technological progress but also heralded a new era of intelligent healthcare. Nowadays, traditional Chinese medicine (TCM) is moving towards the road of intelligent transformation, in which the urgency of integrating the advanced insights of modern medicine is becoming more and more obvious. At the same time, with the full use of various types of artificial intelligence technology, to explore the potential of Chinese medicine, prompting it to embark on a standardized development track, in order to let the ancient Chinese medicine in the wave of modern science and technology renewed new life. Through a systematic exploration utilizing keywords such as “AI”, “TCM”, and “Standardization”, we conducted an extensive search across major repositories including Web of Science, PubMed, CNKI, and other databases, analyzing approximately 1,000 scholarly works. We strive to deepen our understanding of TCM while fully exploiting the integration potential of AI and TCM, and to effectively promote TCM to make great strides towards more scientific, standardized and efficient standardization. This review explores six critical areas where AI techniques such as machine learning (ML) and deep learning (DL) contribute: disease diagnosis, prevention and treatment, herbal medicine quality evaluation, pharmacokinetics, mechanisms of action, and non-drug therapy. Examples include: using ML to predict disease outcomes; modeling pharmacokinetics using DL; and using AI techniques to assess the quality grade of herbal medicines etc.. It examines the systemic responses driven by complex interactions between internal and environmental factors during disease progression, grounded in fundamental human biology. Through rigorous high-throughput screening and analysis, this review elucidates intricate biological interaction networks and achieves comprehensive holistic regulation, thereby furthering the standardization of Traditional Chinese Medicine. This review explores the complex dimensions of TCM using cutting-edge AI techniques to provide strategic guidance for promoting standardization and evolutionary development in the field. (Graphical Abstract)
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