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Overview of Artificial Intelligence Applications in Chinese Medicine Therapy
To evaluate the importance of AI technologies in modernizing traditional Chinese medicine (TCM) therapy, this article presents the systematic review of the relevant literature and explains the beneficial effects of AI technology on the TCM treatment outcomes from the experience of famous and veteran...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7990551/ https://www.ncbi.nlm.nih.gov/pubmed/33815559 http://dx.doi.org/10.1155/2021/6678958 |
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author | Feng, Chuwen Zhou, Shuoyan Qu, Yuanyuan Wang, Qingyong Bao, Shengyong Li, Yang Yang, Tiansong |
author_facet | Feng, Chuwen Zhou, Shuoyan Qu, Yuanyuan Wang, Qingyong Bao, Shengyong Li, Yang Yang, Tiansong |
author_sort | Feng, Chuwen |
collection | PubMed |
description | To evaluate the importance of AI technologies in modernizing traditional Chinese medicine (TCM) therapy, this article presents the systematic review of the relevant literature and explains the beneficial effects of AI technology on the TCM treatment outcomes from the experience of famous and veteran Chinese medicines, including acupuncture, Tui Na massage, and Qigong practitioners. This study also focuses on the urgent necessity to apply AI technologies to develop therapeutic models on the theme “treating the disease before it happens.” Furthermore, the study also discusses the major bottlenecks and future prospects for the development of intelligent TCM treatment strategies. |
format | Online Article Text |
id | pubmed-7990551 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-79905512021-04-01 Overview of Artificial Intelligence Applications in Chinese Medicine Therapy Feng, Chuwen Zhou, Shuoyan Qu, Yuanyuan Wang, Qingyong Bao, Shengyong Li, Yang Yang, Tiansong Evid Based Complement Alternat Med Review Article To evaluate the importance of AI technologies in modernizing traditional Chinese medicine (TCM) therapy, this article presents the systematic review of the relevant literature and explains the beneficial effects of AI technology on the TCM treatment outcomes from the experience of famous and veteran Chinese medicines, including acupuncture, Tui Na massage, and Qigong practitioners. This study also focuses on the urgent necessity to apply AI technologies to develop therapeutic models on the theme “treating the disease before it happens.” Furthermore, the study also discusses the major bottlenecks and future prospects for the development of intelligent TCM treatment strategies. Hindawi 2021-03-17 /pmc/articles/PMC7990551/ /pubmed/33815559 http://dx.doi.org/10.1155/2021/6678958 Text en Copyright © 2021 Chuwen Feng et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Feng, Chuwen Zhou, Shuoyan Qu, Yuanyuan Wang, Qingyong Bao, Shengyong Li, Yang Yang, Tiansong Overview of Artificial Intelligence Applications in Chinese Medicine Therapy |
title | Overview of Artificial Intelligence Applications in Chinese Medicine Therapy |
title_full | Overview of Artificial Intelligence Applications in Chinese Medicine Therapy |
title_fullStr | Overview of Artificial Intelligence Applications in Chinese Medicine Therapy |
title_full_unstemmed | Overview of Artificial Intelligence Applications in Chinese Medicine Therapy |
title_short | Overview of Artificial Intelligence Applications in Chinese Medicine Therapy |
title_sort | overview of artificial intelligence applications in chinese medicine therapy |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7990551/ https://www.ncbi.nlm.nih.gov/pubmed/33815559 http://dx.doi.org/10.1155/2021/6678958 |
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