Data Analytics for Traditional Chinese Medicine Research

ISBN-13: 9783319346298 / Angielski / Miękka / 2016 / 248 str.

Josiah Poon; Simon K. Poon

Opis

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.

Spis treści

Foreword.- 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.