000 04286nam a22005055i 4500
001 978-3-319-03801-8
003 DE-He213
005 20200421112554.0
007 cr nn 008mamaa
008 140219s2014 gw | s |||| 0|eng d
020 _a9783319038018
_9978-3-319-03801-8
024 7 _a10.1007/978-3-319-03801-8
_2doi
050 4 _aQA76.9.D343
072 7 _aUNF
_2bicssc
072 7 _aUYQE
_2bicssc
072 7 _aCOM021030
_2bisacsh
082 0 4 _a006.312
_223
245 1 0 _aData Analytics for Traditional Chinese Medicine Research
_h[electronic resource] /
_cedited by Josiah Poon, Simon K. Poon.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aXII, 248 p. 59 illus., 45 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aForeword -- Searching for Evidence in Traditional Chinese Medicine Research: A Review and New Opportunities -- Causal Complexities of TCM Prescriptions: Understanding the underlying mechanisms of herbal formulation -- Medical Diagnosis by Using Machine Learning Techniques -- Network based deciphering of the mechanism of TCM -- Prescription Analysis and Mining -- Statistical Validation of TCM Syndrome Postulates in the Context of Depressive Patients -- Artificial Neural Network-based Chinese Medicine Diagnosis in Decision Support Manner and Herbal Ingredient Discoveries -- Chromatographic Fingerprinting and Chemometric Techniques for Quality Control of Herb Medicines -- A New Methodology for Uncovering the Bioactive Fractions in Herbal Medicine Using the Approach of Quantitative Pattern-Activity Relationship -- An Innovative and Comprehensive Approach in Studying the Complex Synergistic Interactions Among Herbs in Chinese Herbal Formulae -- Data mining in real-world traditional Chinese medicine clinical data warehouse -- TCM data mining and quality evaluation with SAPHRON(TM) system -- An overview on evidence-based medicine and medical informatics in traditional Chinese medicine practice.
520 _aThis 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.
650 0 _aComputer science.
650 0 _aHealth informatics.
650 0 _aData mining.
650 0 _aPattern recognition.
650 1 4 _aComputer Science.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aHealth Informatics.
650 2 4 _aHealth Informatics.
650 2 4 _aPattern Recognition.
700 1 _aPoon, Josiah.
_eeditor.
700 1 _aK. Poon, Simon.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319038001
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-03801-8
912 _aZDB-2-SCS
942 _cEBK
999 _c59062
_d59062