NDLI: TCM syndromes diagnostic model of hypertension: Study based on Tree Augmented Naive Bayes

Content Provider	IEEE Xplore Digital Library
Author	Wen-wei Ouyang Xiao-zhong Lin Yi Ren Yi Luo Yun-tao Liu Jia-min Yuan Ai-hua Ou Guo-zheng Li
Copyright Year	2011
Description	Author affiliation: Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangzhou (510120), China (Wen-wei Ouyang; Xiao-zhong Lin; Yi Ren; Yi Luo; Yun-tao Liu; Jia-min Yuan)
Abstract	To establish a Bayesian diagnosis model of TCM symptoms by using the hypertension epidemiological Syndrome databases. The Clementine 12.0 software is used to build the Tree Augmented Naive Bayes models, calculate the Bayesian conditional probability, and compare the forecast accuracy of the syndrome diagnosis model. The training sample had 384 cases and calculated 69 symptoms and signs, without prior knowledge, the prediction accuracy rate of the training model are 72.11%, and with the prior knowledge, the testing sample had 384 cases, the prediction accuracy rate of testing model is up to 78.55%. Through the sample study, Bayesian networks can improve the prediction accuracy; we can build a more accurate hypertension diagnosis model through the current work.
Starting Page	834
Ending Page	837
File Size	945139
Page Count	4
File Format	PDF
ISBN	9781457716126
e-ISBN	9781457716133
DOI	10.1109/BIBMW.2011.6112481
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hypertension Accuracy Tongue TAN Bayes Model Bayesian methods TCM Syndrome diagnosis model Predictive models Data models prediction rate Medical diagnostic imaging
Content Type	Text
Resource Type	Article

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