A survey of artificial intelligence in tongue image for disease diagnosis and syndrome differentiation

Abstract

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.

Tongue image fusion and analysis of thermal and visible images in diabetes mellitus using machine learning techniques

“…ResNet50 is a deep CNN architecture that has garnered significant popularity in the field of computer vision, particularly for tasks such as image classification and object detection 47 . The key innovation of ResNet50 lies in the incorporation of residual blocks, aiming to overcome the vanishing gradient problem and facilitate the training of extremely deep neural networks.…”

“…ResNet50 is a deep CNN architecture that has garnered significant popularity in the field of computer vision, particularly for tasks such as image classification and object detection 47…”

Traditional Chinese medicine diagnostic prediction model for holistic syndrome differentiation based on deep learning

“…With growing emphasis on the development of artificial intelligence (AI) for TCM, AI-driven TCM characteristic diagnostic technology of syndrome differentiation may alleviate the scarcity of clinical TCM practitioners, and promote AI development of TCM medical decision-making. 12 , 13 The development of AI in TCM remains in its infancy, and the establishment of an intelligent infrastructure based on deep learning for TCM syndrome is of more paramount significance. 14 , 15 , 16 Several TCM research institutions have integrated AI techniques with distinctive TCM syndrome differentiation, and have achieved better predictive performance of the model in several tasks, such as TCM syndrome prediction, tongue diagnosis, and constitution identification, among others.…”

Tongue image feature classification and gastric disease diagnosis using deep learning in Traditional Chinese medicine

“…The integration of computer vision technology with traditional Chinese medicine theory has garnered considerable interest among researchers in both medical and information fields. Notably, investigations into tongue image features such as color, texture, and other characteristics have yielded valuable insights [4]. For instance, Fang et al [5] conducted a study utilizing a tongue examination device to capture tongue images, employing methods like chromaticity thresholding for tongue segmentation and evaluating metrics such as RGB color space, contrast, entropy, and second-order moment values for texture analysis.…”