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A Network-Based Approach to Investigate the Pattern of Syndrome in Depression
Joint Authors
Gao, Yibo
Chen, Lin
Deng, Qingqiong
Wang, Jialing
Yu, Miao
Guo, Rongjuan
Lu, Peng
Liu, Xi
Dai, Wen
Zhang, Yunling
Song, Jianglong
Source
Evidence-Based Complementary and Alternative Medicine
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-02
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
In Traditional Chinese Medicine theory, syndrome is essential to diagnose diseases and treat patients, and symptom is the foundation of syndrome differentiation.
Thus the combination and interaction between symptoms represent the pattern of syndrome at phenotypic level, which can be modeled and analyzed using complex network.
At first, we collected inquiry information of 364 depression patients from 2007 to 2009.
Next, we learned classification models for 7 syndromes in depression using naïve Bayes, Bayes network, support vector machine (SVM), and C4.5.
Among them, SVM achieves the highest accuracies larger than 0.9 except for Yin deficiency.
Besides, Bayes network outperforms naïve Bayes for all 7 syndromes.
Then key symptoms for each syndrome were selected using Fisher’s score.
Based on these key symptoms, symptom networks for 7 syndromes as well as a global network for depression were constructed through weighted mutual information.
Finally, we employed permutation test to discover dynamic symptom interactions, in order to investigate the difference between syndromes from the perspective of symptom network.
As a result, significant dynamic interactions were quite different for 7 syndromes.
Therefore, symptom networks could facilitate our understanding of the pattern of syndrome and further the improvement of syndrome differentiation in depression.
American Psychological Association (APA)
Song, Jianglong& Liu, Xi& Deng, Qingqiong& Dai, Wen& Gao, Yibo& Chen, Lin…[et al.]. 2015. A Network-Based Approach to Investigate the Pattern of Syndrome in Depression. Evidence-Based Complementary and Alternative Medicine،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1063583
Modern Language Association (MLA)
Song, Jianglong…[et al.]. A Network-Based Approach to Investigate the Pattern of Syndrome in Depression. Evidence-Based Complementary and Alternative Medicine No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1063583
American Medical Association (AMA)
Song, Jianglong& Liu, Xi& Deng, Qingqiong& Dai, Wen& Gao, Yibo& Chen, Lin…[et al.]. A Network-Based Approach to Investigate the Pattern of Syndrome in Depression. Evidence-Based Complementary and Alternative Medicine. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1063583
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1063583