Development and Application of Traditional Chinese Medicine Using AI Machine Learning and Deep Learning Strategies.

The American journal of Chinese medicine Pub Date : 2024-01-01 Epub Date: 2024-05-08 DOI:10.1142/S0192415X24500265
Danping Pan, Yilei Guo, Yongfu Fan, Haitong Wan
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引用次数: 0

Abstract

Traditional Chinese medicine (TCM) has been used for thousands of years and has been proven to be effective at treating many complicated illnesses with minimal side effects. The application and advancement of TCM are, however, constrained by the absence of objective measuring standards due to its relatively abstract diagnostic methods and syndrome differentiation theories. Ongoing developments in machine learning (ML) and deep learning (DL), specifically in computer vision (CV) and natural language processing (NLP), offer novel opportunities to modernize TCM by exploring the profound connotations of its theory. This review begins with an overview of the ML and DL methods employed in TCM; this is followed by practical instances of these applications. Furthermore, extensive discussions emphasize the mature integration of ML and DL in TCM, such as tongue diagnosis, pulse diagnosis, and syndrome differentiation treatment, highlighting their early successful application in the TCM field. Finally, this study validates the accomplishments and addresses the problems and challenges posed by the application and development of TCM powered by ML and DL. As ML and DL techniques continue to evolve, modern technology will spark new advances in TCM.

利用人工智能机器学习和深度学习策略开发和应用传统中医药。
传统中医药(TCM)已有数千年的历史,被证明能有效治疗多种疑难杂症,且副作用极小。然而,由于中医的诊断方法和辨证理论相对抽象,缺乏客观的衡量标准,制约了中医的应用和发展。机器学习(ML)和深度学习(DL),特别是计算机视觉(CV)和自然语言处理(NLP)的不断发展,为探索中医理论的深刻内涵,实现中医现代化提供了新的机遇。本综述首先概述了中医中采用的 ML 和 DL 方法,然后介绍了这些应用的实际案例。此外,大量的论述强调了 ML 和 DL 在中医中的成熟整合,如舌诊、脉诊和辨证论治,突出了它们在中医领域的早期成功应用。最后,本研究验证了这些成就,并探讨了以 ML 和 DL 为动力的中医药应用与发展所面临的问题和挑战。随着 ML 和 DL 技术的不断发展,现代技术将为中医药带来新的进步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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