Application of data mining technology in analysis of characteristics of Chinese medicine to treat cervical spondylotic myelopathy

Author

Shuan Wu ; Ruimin Tian ; Shudong Chen ; Dongyi Chen ; Ping Chen

Author_Institution

Integrative Med. Hosp. of Guangdong Province, Foshan, China

fYear

2013

fDate

18-21 Dec. 2013

Firstpage

232

Lastpage

235

Abstract

Cervical spondylotic myelopathy(CSM) is one kind of refractory diseases, with high rate of disability. Chinese medicine treatment has certain effects on delaying the process of CSM or its palindromia, and herbs are one of the most effective methods of conservative treatment. This paper presents a study on using data mining to explore the association rules among herbs used to treat CSM. By analyzing the papers of Chinese treatment of CSM and exploring the characteristics of herbs, we found that herbs usually used to treat CSM are Radix Angelicae Sinensis, Rhizoma Chuanxiong, Radix Astragali, Radix Salviae Miltiorrhizae, Radix Rehmanniae Preparata, Radix Glycyrrhizae, Poria, Radix Paeoniae Rubra, Flos Carthami, Radix Puerariae and Radix Paeoniae Alba. Besides, their effective rule support degree is more than 5.0% and confidence is more than 80%, indicating strong correlation.

Keywords

bone; data mining; diseases; medical computing; medical disorders; neurophysiology; orthopaedics; patient treatment; CSM process; Chinese medicine treatment; cervical spondylotic myelopathy treatment; data mining technology application; herbs; palindromia; refractory diseases; Association rules; Blood; Correlation; Diseases; Educational institutions; Spinal cord; Cervical Spondylotic Myelopathy; Chinese Medicine; Data Mining Technology;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on

Conference_Location

Shanghai

Type

conf

DOI

10.1109/BIBM.2013.6732681

Filename

6732681