Abstract
Prescription analysis is an important task in traditional Chinese medicine (TCM), both in theoretical development and clinical practices. However, with the rapid development of TCM researches, massive literature collected in databases blocks end users from acquiring general knowledge of prescriptions. Fortunately, with the rapid development of text mining technology, now, it is possible to extract associated networks focused on prescriptions. In this chapter, focused on Liuwei- Dihuang formula as an example, by executing discrete derivative algorithm in the text mining process, prescription associated networks are mined out. These networks include prescription-pattern-disease, prescription-disease-Chinese herbal medicine, prescription-pattern-Chinese herbal medicine, prescription-Chinese herbal medicine-symptom, and prescription-pattern-symptom. These networks might be good references for TCM research and clinical practices.
Original language | English |
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Title of host publication | Data Analytics for Traditional Chinese Medicine Research |
Editors | Josiah Poon, Simon K. Poon |
Publisher | Springer Cham |
Pages | 97-109 |
Number of pages | 13 |
Edition | 1st |
ISBN (Electronic) | 9783319038018 |
ISBN (Print) | 9783319038001, 9783319346298 |
DOIs | |
Publication status | Published - 5 Jan 2014 |
Scopus Subject Areas
- General Computer Science
User-Defined Keywords
- Traditional Chinese Medicine
- Herbal Medicine
- Western Medicine
- Text Mining
- Chinese Herbal Medicine