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Quantitative knowledge presentation models of traditional Chinese medicine (TCM): A review

Journal

ARTIFICIAL INTELLIGENCE IN MEDICINE
Volume 103, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.artmed.2020.101810

Keywords

TCM; Quantitative model; Research progress; Yin-Yang Wu-Xing; Patterns of TCM prescriptions; Data mining

Funding

  1. National Natural Science Foundation of China [71571090, 61772019, 81774218]
  2. Youth Innovation Team of Shaanxi Universities
  3. Fundamental Research Funds for the Central Universities [JB190602]
  4. Interdisciplinary Foundation of Humanities and Information [RW180167]
  5. Guangdong education department [2018GWQNCX050]

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Modern computer technology sheds light on new ways of innovating Traditional Chinese Medicine (TCM). One method that gets increasing attention is the quantitative research method, which makes use of data mining and artificial intelligence technology as well as the mathematical principles in the research on rationales, academic viewpoints of famous doctors of TCM, dialectical treatment by TCM, clinical technology of TCM, the patterns of TCM prescriptions, clinical curative effects of TCM and other aspects. This paper reviews the methods, means, progress and achievements of quantitative research on TCM. In the core database of the Web of Science, Traditional Chinese Medicine, Computational Science and Mathematical Computational Biology are selected as the main retrieval fields, and the retrieval time interval from 1999 to 2019 is used to collect relevant literature. It is found that researchers from China Academy of Chinese Medical Sciences, Zhejiang University, Chinese Academy of Sciences and other institutes have opened up new methods of research on TCM since 2009, with quantitative methods and knowledge presentation models. The adopted tools mainly consist of text mining, knowledge discovery, technologies of the TCM database, data mining and drug discovery through TCM calculation, etc. In the future, research on quantitative models of TCM will focus on solving the heterogeneity and incompleteness of big data of TCM, establishing standardized treatment systems, and promoting the development of modernization and internationalization of TCM.

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