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...

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Bibliographic Details
Published in:DIGITAL HEALTH Vol. 9; p. 20552076231191044
Main Authors: Liu, Qi, Li, Yan, Yang, Peng, Liu, Quanquan, Wang, Chunbao, Chen, Keji, Wu, Zhengzhi
Format: Book Review Journal Article
Language:English
Published: London, England SAGE Publications 01-01-2023
Sage Publications Ltd
SAGE Publishing
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Summary: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.
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QL and YL contributed equally to this work.
ISSN:2055-2076
2055-2076
DOI:10.1177/20552076231191044