Data-driven based four examinations in TCM: a survey
10.1016/j.dcmed.2022.12.004
- Author:
Dong SUI
1
;
Lei ZHANG
2
;
Fei YANG
3
Author Information
1. School of Electrical and Information Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100083, China
2. Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, MD 21201, USA
3. School of Mechanical Electrical and Information Engineering, Shandong University, Weihai, Shandong 264209, China
- Publication Type:Review
- Keywords:
Traditional Chinese medicine (TCM);
Four examinations;
Data-driven;
Machine learning;
Computational intelligence
- From:
Digital Chinese Medicine
2022;5(4):377-385
- CountryChina
- Language:English
-
Abstract:
Traditional Chinese medicine (TCM) diagnosis is a unique disease diagnosis method with thousands of years of TCM theory and effective experience. Its thinking mode in the process is different from that of modern medicine, which includes the essence of TCM theory. From the perspective of clinical application, the four diagnostic methods of TCM, including inspection, auscultation and olfaction, inquiry, and palpation, have been widely accepted by TCM practitioners worldwide. With the rise of artificial intelligence (AI) over the past decades, AI based TCM diagnosis has also grown rapidly, marked by the emerging of a large number of data-driven deep learning models. In this paper, our aim is to simply but systematically review the development of the data-driven technologies applied to the four diagnostic approaches, i.e. the four examinations, in TCM, including data sets, digital signal acquisition devices, and learning based computational algorithms, to better analyze the development of AI-based TCM diagnosis, and provide references for new research and its applications in TCM settings in the future.
- Full text:suidong.pdf
