舌头
计算机科学
人工智能
深度学习
领域(数学)
透视图(图形)
分割
可靠性(半导体)
图像分割
集合(抽象数据类型)
机器学习
医学
病理
功率(物理)
物理
数学
量子力学
纯数学
程序设计语言
作者
Qi Liu,Yan Li,Yang Peng,Quanquan Liu,Chunbao Wang,Keji Chen,Zhengzhi Wu
标识
DOI:10.1177/20552076231191044
摘要
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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