Data Analytics for Traditional Chinese Medicine Research

1. Front Matter

   Pages i-xii

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2. Searching for Evidence in Traditional Chinese Medicine Research: A Review and New Opportunities

   • Simon K. Poon, Shagun Goyal, Albert Cheng, Josiah Poon

   Pages 1-16

3. Causal Complexities of TCM Prescriptions: Understanding the Underlying Mechanisms of Herbal Formulation

   • Simon K. Poon, Alan Su, Lily Chau, Josiah Poon

   Pages 17-38

4. Medical Diagnosis by Using Machine Learning Techniques

   • Mingyu You, Guo-Zheng Li

   Pages 39-79

5. Network Based Deciphering of the Mechanism of TCM

   • Yi Sun, Qi Liu, Zhiwei Cao

   Pages 81-96

6. Prescription Analysis and Mining

   • Guang Zheng, Miao Jiang, Cheng Lu, Aiping Lu

   Pages 97-109

7. Statistical Validation of TCM Syndrome Postulates in the Context of Depressive Patients

   • Yan Zhao, Nevin L. Zhang, Tianfang Wang, Qingguo Wang, Tengfei Liu

   Pages 111-121

8. Artificial Neural Network Based Chinese Medicine Diagnosis in Decision Support Manner and Herbal Ingredient Discoveries

   • Wilfred Lin, Jackei Wong

   Pages 123-132

9. Chromatographic Fingerprinting and Chemometric Techniques for Quality Control of Herb Medicines

   • Zhimin Zhang, Yizeng Liang, Peishan Xie, Footim Chau, Kelvin Chan

   Pages 133-153

10. A New Methodology for Uncovering the Bioactive Fractions in Herbal Medicine Using the Approach of Quantitative Pattern-Activity Relationship

    • Foo-tim Chau, Qing-song Xu, Daniel Man-yuen Sze, Hoi-yan Chan, Tsui-yan Lau, Da-lin Yuan et al.

    Pages 155-172

11. An Innovative and Comprehensive Approach in Studying the Complex Synergistic Interactions Among Herbs in Chinese Herbal Formulae

    • Chun-Hay Ko, Lily Chau, David Wing-Shing Cheung, Johnny Chi-Man Koon, Kwok-Pui Fung, Ping-Chung Leung et al.

    Pages 173-188

12. Data Mining in Real-World Traditional Chinese Medicine Clinical Data Warehouse

    • Xuezhong Zhou, Baoyan Liu, Xiaoping Zhang, Qi Xie, Runshun Zhang, Yinghui Wang et al.

    Pages 189-213

13. TCM Data Mining and Quality Evaluation with SAPHRONTM System

    • Jing Yang, Hua Su, Guoshun Tang, Zihan Zheng, Yue Shen, Lei Zhang et al.

    Pages 215-226

14. An Overview on Evidence-Based Medicine and Medical Informatics in Traditional Chinese Medicine Practice

    • Kelvin Chan, Josiah Poon, Simon K. Poon, Miao Jiang, Aiping Lu

    Pages 227-248

This contributed volume explores how data mining, machine learning, and similar statistical techniques can analyze the types of problems arising from Traditional Chinese Medicine (TCM) research. The book focuses on the study of clinical data and the analysis of herbal data. Challenges addressed include diagnosis, prescription analysis, ingredient discoveries, network based mechanism deciphering, pattern-activity relationships, and medical informatics. Each author demonstrates how they made use of machine learning, data mining, statistics and other analytic techniques to resolve their research challenges, how successful if these techniques were applied, any insight noted and how these insights define the most appropriate future work to be carried out. Readers are given an opportunity to understand the complexity of diagnosis and treatment decision, the difficulty of modeling of efficacy in terms of herbs, the identification of constituent compounds in an herb, the relationship between these compounds and biological outcome so that evidence-based predictions can be made. Drawing on a wide range of experienced contributors, Data Analytics for Traditional Chinese Medicine Research is a valuable reference for professionals and researchers working in health informatics and data mining. The techniques are also useful for biostatisticians and health practitioners interested in traditional medicine and data analytics.

• Chemometrics
• Clinical data
• Data analytics
• Data warehouse
• Evidence-based
• Herbal network
• Interaction
• Pattern-activity relationship
• Synergy
• Traditional Chinese Medicine

• University of Sydney, Sydney, Australia

  Josiah Poon, Simon K. Poon

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