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A survey of artificial intelligence in tongue image for disease diagnosis and syndrome differentiation
The rapid development of artificial intelligence technology has gradually extended from the general field to all walks of life, and intelligent tongue diagnosis is the product of a miraculous connection between this new discipline and traditional disciplines. We reviewed the deep learning methods an...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10408356/ https://www.ncbi.nlm.nih.gov/pubmed/37559828 http://dx.doi.org/10.1177/20552076231191044 |
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author | Liu, Qi Li, Yan Yang, Peng Liu, Quanquan Wang, Chunbao Chen, Keji Wu, Zhengzhi |
author_facet | Liu, Qi Li, Yan Yang, Peng Liu, Quanquan Wang, Chunbao Chen, Keji Wu, Zhengzhi |
author_sort | Liu, Qi |
collection | PubMed |
description | The rapid development of artificial intelligence technology has gradually extended from the general field to all walks of life, and intelligent tongue diagnosis is the product of a miraculous connection between this new discipline and traditional disciplines. We reviewed the deep learning methods and machine learning applied in tongue image analysis that have been studied in the last 5 years, focusing on tongue image calibration, detection, segmentation, and classification of diseases, syndromes, and symptoms/signs. Introducing technical evolutions or emerging technologies were applied in tongue image analysis; as we have noticed, attention mechanism, multiscale features, and prior knowledge were successfully applied in it, and we emphasized the value of combining deep learning with traditional methods. We also pointed out two major problems concerned with data set construction and the low reliability of performance evaluation that exist in this field based on the basic essence of tongue diagnosis in traditional Chinese medicine. Finally, a perspective on the future of intelligent tongue diagnosis was presented; we believe that the self-supervised method, multimodal information fusion, and the study of tongue pathology will have great research significance. |
format | Online Article Text |
id | pubmed-10408356 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-104083562023-08-09 A survey of artificial intelligence in tongue image for disease diagnosis and syndrome differentiation Liu, Qi Li, Yan Yang, Peng Liu, Quanquan Wang, Chunbao Chen, Keji Wu, Zhengzhi Digit Health Review Article The rapid development of artificial intelligence technology has gradually extended from the general field to all walks of life, and intelligent tongue diagnosis is the product of a miraculous connection between this new discipline and traditional disciplines. We reviewed the deep learning methods and machine learning applied in tongue image analysis that have been studied in the last 5 years, focusing on tongue image calibration, detection, segmentation, and classification of diseases, syndromes, and symptoms/signs. Introducing technical evolutions or emerging technologies were applied in tongue image analysis; as we have noticed, attention mechanism, multiscale features, and prior knowledge were successfully applied in it, and we emphasized the value of combining deep learning with traditional methods. We also pointed out two major problems concerned with data set construction and the low reliability of performance evaluation that exist in this field based on the basic essence of tongue diagnosis in traditional Chinese medicine. Finally, a perspective on the future of intelligent tongue diagnosis was presented; we believe that the self-supervised method, multimodal information fusion, and the study of tongue pathology will have great research significance. SAGE Publications 2023-08-06 /pmc/articles/PMC10408356/ /pubmed/37559828 http://dx.doi.org/10.1177/20552076231191044 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License (https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits non-commercial use, reproduction and distribution of the work as published without adaptation or alteration, without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Review Article Liu, Qi Li, Yan Yang, Peng Liu, Quanquan Wang, Chunbao Chen, Keji Wu, Zhengzhi A survey of artificial intelligence in tongue image for disease diagnosis and syndrome differentiation |
title | A survey of artificial intelligence in tongue image for disease diagnosis and syndrome differentiation |
title_full | A survey of artificial intelligence in tongue image for disease diagnosis and syndrome differentiation |
title_fullStr | A survey of artificial intelligence in tongue image for disease diagnosis and syndrome differentiation |
title_full_unstemmed | A survey of artificial intelligence in tongue image for disease diagnosis and syndrome differentiation |
title_short | A survey of artificial intelligence in tongue image for disease diagnosis and syndrome differentiation |
title_sort | survey of artificial intelligence in tongue image for disease diagnosis and syndrome differentiation |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10408356/ https://www.ncbi.nlm.nih.gov/pubmed/37559828 http://dx.doi.org/10.1177/20552076231191044 |
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