Data Analytics for Traditional Chinese Medicine Research
Poon, Josiah, K. Poon, Simon (Eds.)
2014, XII, 248 p. 59 illus., 45 illus. in color.
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Presents a data analytic approach for an efficient way to analyze the data, to find useful patterns, to generate and validate hypothesis
Offers data mining researchers a new domain of study, an area which sits on a wealth of data untouched for development of new algorithms to address the specific nature of this field
Provides the biostatistics community and health practitioners a means to analyze Traditional Chinese Medicine (TCM)
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.
Content Level »Research
Keywords »Chemometrics - Clinical data - Data analytics - Data warehouse - Evidence-based - Herbal network - Interaction - Pattern-activity relationship - Synergy - Traditional Chinese Medicine