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- W4323029700 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." @default.
- W4323029700 created "2023-03-04" @default.
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- W4323029700 date "2022-12-01" @default.
- W4323029700 modified "2023-10-11" @default.
- W4323029700 title "Data-driven based four examinations in TCM: a survey" @default.
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- W4323029700 doi "https://doi.org/10.1016/j.dcmed.2022.12.004" @default.
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