Evidence-Based Complementary and Alternative Medicine

Evidence-Based Patient Classification for Traditional Chinese Medicine


Publishing date
27 Mar 2015
Status
Published
Submission deadline
07 Nov 2014

Lead Editor

1Tongji University, Shanghai, China

2The University of Hong Kong, Hong Kong

3The University of Sydney, Sydney, Australia


Evidence-Based Patient Classification for Traditional Chinese Medicine

Description

Effective use of traditional Chinese medicine (TCM) treatments requires syndrome differentiation where patients suffering from a western medicine disease are divided into several classes based on their symptoms and signs, and different TCM treatments are applied to patients in different proper patient classification which is important not only for clinic uniformity and efficacy, but also for research endeavors to evaluate syndrome-oriented treatment plans or to gain biomedical understanding of various syndrome types.

TCM patient classification is a challenging problem as there are no gold standards to rely on. Nonetheless, fruitful investigations have been conducted on several fronts.

Potential topics include, but are not limited to:

  • Establishment of classification standards for particular diseases
  • Extraction of classification rules from data labeled by experts
  • Detection of symptom cooccurrence patterns from unlabeled data and use of such patterns to define syndrome types
  • Evidence-based pulse and tongue classification
  • Biomedical research on particular syndrome types

This special issue aims at showing the state of the art of research on evidence-based TCM patient classification. We welcome original research articles as well as review articles on the topics listed above and other related issues.


Articles

  • Special Issue
  • - Volume 2015
  • - Article ID 168343
  • - Editorial

Evidence-Based Patient Classification for Traditional Chinese Medicine

Guo-Zheng Li | Ka-Fai Chung | Josiah Poon
  • Special Issue
  • - Volume 2015
  • - Article ID 897580
  • - Research Article

Significant Geometry Features in Tongue Image Analysis

Bob Zhang | Han Zhang
  • Special Issue
  • - Volume 2015
  • - Article ID 376716
  • - Review Article

Advances in Patient Classification for Traditional Chinese Medicine: A Machine Learning Perspective

Changbo Zhao | Guo-Zheng Li | ... | Jinling Niu
  • Special Issue
  • - Volume 2015
  • - Article ID 936290
  • - Research Article

A Novel Classification Method for Syndrome Differentiation of Patients with AIDS

Yufeng Zhao | Liyun He | ... | Xianghong Jing
  • Special Issue
  • - Volume 2015
  • - Article ID 751743
  • - Review Article

Correlations between Phlegm Syndrome of Chinese Medicine and Coronary Angiography: A Systematic Review and Meta-Analysis

Qiu-Yan Zhang | Hao Liang | ... | Xiang Sun
  • Special Issue
  • - Volume 2015
  • - Article ID 503536
  • - Research Article

Cerebral Activity Changes in Different Traditional Chinese Medicine Patterns of Psychogenic Erectile Dysfunction Patients

Qi Liu | Peihai Zhang | ... | Degui Chang
  • Special Issue
  • - Volume 2015
  • - Article ID 160189
  • - Review Article

Prescription of Chinese Herbal Medicine in Pattern-Based Traditional Chinese Medicine Treatment for Depression: A Systematic Review

Wing-Fai Yeung | Ka-Fai Chung | ... | Eric Tat-Chi Ziea
  • Special Issue
  • - Volume 2015
  • - Article ID 895749
  • - Research Article

Analysis and Recognition of Traditional Chinese Medicine Pulse Based on the Hilbert-Huang Transform and Random Forest in Patients with Coronary Heart Disease

Rui Guo | Yiqin Wang | ... | Wenjie Xu
  • Special Issue
  • - Volume 2015
  • - Article ID 940898
  • - Research Article

Yang Deficiency Body Constitution Acts as a Predictor of Diabetic Retinopathy in Patients with Type 2 Diabetes: Taichung Diabetic Body Constitution Study

Cheng-Hung Lee | Tsai-Chung Li | ... | Yi-Chang Su
  • Special Issue
  • - Volume 2015
  • - Article ID 435085
  • - Research Article

Mining Symptom-Herb Patterns from Patient Records Using Tripartite Graph

Jinpeng Chen | Josiah Poon | ... | Daniel M. Y. Sze
Evidence-Based Complementary and Alternative Medicine
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Acceptance rate7%
Submission to final decision145 days
Acceptance to publication29 days
CiteScore3.500
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Impact Factor-
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