Paper Info
Title
The Predictive Role of Symptoms/signs on ACR20 Responses in Rheumatoid Arthritis Analyzed with Data Mining Approaches
Abstract
Objective: The role of symptoms/signs for American College of Rheumatology 20% response (ACR20) prediction in rheumatoid arthritis (RA) analyzed with decision tree and neuron network was explored. Methods: 489 patients were randomly divided to receive Western medicine (WM) therapy, 247 cases; and traditional Chinese medicine (CM) therapy (TCM), 242 cases. ACR20 response was employed as effectiveness evaluation point. The symptoms/signs at baseline were collected and analyzed for ACR20 response prediction with decision tree and neural network methods, and 75% data were for training and 25% data for verification set. Results: 19 symptoms/signs in CM treated patients and 26 in WM treated patients were obtained from MANTELHAENSZEL test or Fisher's exact test (p<0.2 as inclusion criteria) for decision tree analysis, and the ACR20 responses were different in the different combinations of the symptoms/signs both in CM and WM. The results were verified in the verification data sets. For neural network analysis, the training data from CM and WM treated patients were put into the neuron network model, and the Lift Chart was created which showed that the total effective rate could be predicted to be 80% if only right 10 percentage of patients where treated based on the chosen symptoms/signs in CM, and to be 98% if 20% percentage of patients where treated based on the chosen symptoms/signs in WM. Conclusion: Symptoms/signs from TCM have predictive roles for ACR20 response evaluation in RA.
Year
DOI
Venue
2009
10.1109/BMEI.2009.5302485
BMEI
Keywords
Field
DocType
neural network,fisher exact test,acr20 response,symptoms,signs,diseases,western medicine therapy,traditional chinese medicine therapy,mantel-haenszel test,rheumatoid arthritis,data mining,medical computing,decision tree,decision trees,neural nets,mantel haenszel test,neuronal network,traditional chinese medicine,exact test
Training set,Fisher's exact test,Neural network analysis,Data mining,Cochran–Mantel–Haenszel statistics,Internal medicine,Exact test,Traditional Chinese medicine,Rheumatoid arthritis,Rheumatology,Medicine
Conference
ISSN
ISBN
Citations 
1948-2914
978-1-4244-4134-1
0
PageRank 
References 
Authors
0.34
2
8
Name
Order
Citations
PageRank
Qinglin Zha1183.19
Yiting He2191.31
Xiaorong Ding3994.66
Miao Jiang46312.07
Xuewen Liu500.34
Cheng Lu694.97
Ian Tsang700.34
Aiping Lu89423.84