Abstract

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Title:: Advances in the application of artificial intelligence in traditional Chinese medicine diagnosis

Author(s):: LUO Siyan1; 2; WANG Xinzhou3; RAO Xiangrong1; 1. Department of Nephrology, Guanganmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China 2. Guanganmen Hospital, Beijing University of Chinese Medicine, Beijing 100029, China 3. College of Electronic and Information Engineering, Tongji University, Shanghai 201804, China

Keywords:: Keywords: artificial intelligence 4 diagnostic methods of traditional Chinese medicine deep learning review

Abstract:: Abstract: Based on the mathematical principles of various artificial intelligence algorithms, the current situation and problems of artificial intelligence application in traditional Chinese medicine (TCM) diagnosis is expounded. The traditional machine learning algorithms, such as support vector machines and Bayesian algorithms, have high accuracy and robustness in auscultation, inquiry and other scenarios because of their characteristic of small sample learning. Some deep learning algorithms emerging in recent years which can process unstructured data such as images, audio signals, texts, etc. are suitable for scenarios such as inspection and palpation. Multi-modal deep learning can fully mine the information in the data of inspection, auscultation, inquiry and palpation, and perform implicit analysis of 4 TCM diagnostic methods in the feature space. The introduction of artificial intelligence can further promote the objective and quantitative development of TCM, but its data-driven nature requires further standardization of the current TCM database establishment.