Prescription analysis and mining

Guang Zheng, Miao Jiang, Cheng Lu, Aiping LYU*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingChapterpeer-review

6 Citations (Scopus)

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 languageEnglish
Title of host publicationData Analytics for Traditional Chinese Medicine Research
PublisherSpringer International Publishing
Pages97-109
Number of pages13
Volume9783319038018
ISBN (Electronic)9783319038018
ISBN (Print)3319038001, 9783319038001
DOIs
Publication statusPublished - 1 Dec 2014

Scopus Subject Areas

  • Computer Science(all)

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