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.
|Title of host publication||Data Analytics for Traditional Chinese Medicine Research|
|Publisher||Springer International Publishing|
|Number of pages||13|
|ISBN (Print)||3319038001, 9783319038001|
|Publication status||Published - 1 Dec 2014|
Scopus Subject Areas
- Computer Science(all)