TY - GEN
T1 - Exploring the associating rules of prescription and syndrome on Radix Astragali with text mining
AU - Sun, Shuyu
AU - Yu, Changyuan
AU - Jiang, Miao
AU - Wang, Minzhi
AU - He, Xiaojuan
AU - LYU, Aiping
AU - Zheng, Guang
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - Single Chinese herbal medicine (CHM) is the basic element in the formulae of traditional Chinese medicine (TCM). How to acquire knowledge of a single CHM within the framework of TCM is a meaningful task. In TCM, Radix Astragali (RA) is frequently and widely used in clinical practice. In order to explore the associating rules between prescription and syndrome on RA with text mining technique, we downloaded the data set on RA from Chinese BioMedical literature database (also called SinoMed). Then, the rules of prescription corresponding to disease and syndrome on RA were mined out by executing data slicing algorithms. The mining results were visually demonstrated with software Cytoscape 2.8. Text mining, together with artificial reading for anti-noising and validation, is an important approach in exploring the rules of prescription corresponding to disease and syndrome. The results showed that RA was usually used in treating diseases of diabetes and cancers. For them, blood stasis due to qi deficiency was the main syndrome in TCM. Moreover, the results demonstrated associations among TCM syndrome, diseases and formulae associated with RA. These associated networks represented a variety of knowledge items which embodied the associating rules between prescription and syndrome on RA.
AB - Single Chinese herbal medicine (CHM) is the basic element in the formulae of traditional Chinese medicine (TCM). How to acquire knowledge of a single CHM within the framework of TCM is a meaningful task. In TCM, Radix Astragali (RA) is frequently and widely used in clinical practice. In order to explore the associating rules between prescription and syndrome on RA with text mining technique, we downloaded the data set on RA from Chinese BioMedical literature database (also called SinoMed). Then, the rules of prescription corresponding to disease and syndrome on RA were mined out by executing data slicing algorithms. The mining results were visually demonstrated with software Cytoscape 2.8. Text mining, together with artificial reading for anti-noising and validation, is an important approach in exploring the rules of prescription corresponding to disease and syndrome. The results showed that RA was usually used in treating diseases of diabetes and cancers. For them, blood stasis due to qi deficiency was the main syndrome in TCM. Moreover, the results demonstrated associations among TCM syndrome, diseases and formulae associated with RA. These associated networks represented a variety of knowledge items which embodied the associating rules between prescription and syndrome on RA.
KW - associating rules
KW - Data slicing algorithm
KW - Radix Astragali
KW - Text mining
UR - http://www.scopus.com/inward/record.url?scp=84881535313&partnerID=8YFLogxK
U2 - 10.1109/ICCME.2013.6548222
DO - 10.1109/ICCME.2013.6548222
M3 - Conference proceeding
AN - SCOPUS:84881535313
SN - 9781467329699
T3 - 2013 ICME International Conference on Complex Medical Engineering, CME 2013
SP - 115
EP - 118
BT - 2013 ICME International Conference on Complex Medical Engineering, CME 2013
T2 - 2013 7th ICME International Conference on Complex Medical Engineering, CME 2013
Y2 - 25 May 2013 through 28 May 2013
ER -
