Paper Info
Title
Application of data mining technology in excavating prevention and treatment experience of infectious diseases from famous herbalist doctors
Abstract
This study is to explore effect and significance of data mining technology (DMT) used in excavating prevention and treatment experience of infectious diseases from famous herbalist doctors (FHDs). DMT methods such as cluster analysis and association rules was applied to the study on FHDs literature on preventing and treating influenza, dysentery, tuberculosis, viral hepatitis and other infectious diseases in order to excavate the inner rules and refine the regular understanding. The result shows that cluster analysis is helpful to summarize the common understanding of experience including concept of syndrome differentiation, regulation of diagnosis and treatment, prescription characteristic, which based on FHDs' prevention and treatment of influenza (including A H1N1), viral hepatitis and other infectious diseases. Association rules greatly contributed to the judgment of relationship between etiology, syndrome, symptoms and herbal prescription of infectious diseases. In conclusion, DMT provides technical support for concise and inheritance of academic thought which originates from FHDs. DMT is of high application value in research of experience of FHDs and relevant literature, and is worth further discussion.
Year
DOI
Venue
2011
10.1109/BIBMW.2011.6112472
BIBM Workshops
Keywords
Field
DocType
health care,prevention and treatment experience of infectious diseases,symptoms,famous herbalist doctors,diseases,tuberculosis,infectious disease,viral hepatitis,herbal prescription,association rule,famous herbalist doctor,infectious disease treatment experience,influenza,dmt method,fhds literature,data mining,cluster analysis,syndrome differentiation,infectious disease prevention,common understanding,dysentery,association rules,treatment experience,data mining technology,patient treatment,etiology,prescription characteristic
Health care,Data mining,Computer science,Association rule learning,Etiology,Technical support,Tuberculosis,Viral hepatitis,Medical prescription,Patient treatment
Conference
ISSN
ISBN
Citations 
2163-6966
978-1-4577-1612-6
0
PageRank 
References 
Authors
0.34
0
9
Name
Order
Citations
PageRank
Yi Luo101.35
Ji-Qiang Li200.34
Danwen Zheng300.68
Zhanpeng Tan400.68
Hong Zhou500.34
Qingping Deng6142.29
Yuntao Liu701.01
Ai-hua Ou813.86
Jian Yin986197.01