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Development and Application of Traditional Chinese Medicine Using AI Machine Learning and Deep Learning Strategies.
Pan, Danping; Guo, Yilei; Fan, Yongfu; Wan, Haitong.
Afiliación
  • Pan D; School of Basic Medicine Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, P. R. China.
  • Guo Y; School of Basic Medicine Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, P. R. China.
  • Fan Y; School of Basic Medicine Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, P. R. China.
  • Wan H; School of Basic Medicine Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, P. R. China.
Am J Chin Med ; 52(3): 605-623, 2024.
Article en En | MEDLINE | ID: mdl-38715181
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Automático / Aprendizaje Profundo / Medicina Tradicional China Límite: Humans Idioma: En Revista: Am J Chin Med Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Automático / Aprendizaje Profundo / Medicina Tradicional China Límite: Humans Idioma: En Revista: Am J Chin Med Año: 2024 Tipo del documento: Article
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