An Ensemble Learning Based Framework for Traditional Chinese Medicine Data Analysis with ICD-10 Labels
Joint Authors
Huang, Yonghui
Zhong, Ling
Zhang, Yi
Zhang, Gang
Li, Zi-ping
Ou, Shanxing
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-01
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Objective.
This study aims to establish a model to analyze clinical experience of TCM veteran doctors.
We propose an ensemble learning based framework to analyze clinical records with ICD-10 labels information for effective diagnosis and acupoints recommendation.
Methods.
We propose an ensemble learning framework for the analysis task.
A set of base learners composed of decision tree (DT) and support vector machine (SVM) are trained by bootstrapping the training dataset.
The base learners are sorted by accuracy and diversity through nondominated sort (NDS) algorithm and combined through a deep ensemble learning strategy.
Results.
We evaluate the proposed method with comparison to two currently successful methods on a clinical diagnosis dataset with manually labeled ICD-10 information.
ICD-10 label annotation and acupoints recommendation are evaluated for three methods.
The proposed method achieves an accuracy rate of 88.2% ± 2.8% measured by zero-one loss for the first evaluation session and 79.6% ± 3.6% measured by Hamming loss, which are superior to the other two methods.
Conclusion.
The proposed ensemble model can effectively model the implied knowledge and experience in historic clinical data records.
The computational cost of training a set of base learners is relatively low.
American Psychological Association (APA)
Zhang, Gang& Huang, Yonghui& Zhong, Ling& Ou, Shanxing& Zhang, Yi& Li, Zi-ping. 2015. An Ensemble Learning Based Framework for Traditional Chinese Medicine Data Analysis with ICD-10 Labels. The Scientific World Journal،Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1078853
Modern Language Association (MLA)
Zhang, Gang…[et al.]. An Ensemble Learning Based Framework for Traditional Chinese Medicine Data Analysis with ICD-10 Labels. The Scientific World Journal No. 2015 (2015), pp.1-8.
https://search.emarefa.net/detail/BIM-1078853
American Medical Association (AMA)
Zhang, Gang& Huang, Yonghui& Zhong, Ling& Ou, Shanxing& Zhang, Yi& Li, Zi-ping. An Ensemble Learning Based Framework for Traditional Chinese Medicine Data Analysis with ICD-10 Labels. The Scientific World Journal. 2015. Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1078853
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1078853