| 書目名稱 | Data Analytics for Traditional Chinese Medicine Research | | 編輯 | Josiah Poon,Simon K. Poon | | 視頻video | http://file.papertrans.cn/263/262709/262709.mp4 | | 概述 | 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 w | | 圖書封面 |  | | 描述 | 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 | | 出版日期 | Book 2014 | | 關(guān)鍵詞 | Chemometrics; Clinical data; Data analytics; Data warehouse; Evidence-based; Herbal network; Interaction; P | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-03801-8 | | isbn_softcover | 978-3-319-34629-8 | | isbn_ebook | 978-3-319-03801-8 | | copyright | Springer International Publishing Switzerland 2014 |
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