Knowledge-Driven Medicine: A Machine Learning Approach

R. Bharat Rao, Glenn Fung, Romer Rosales

June 15, 2017 Forthcoming by CRC Press
Reference - 300 Pages - 100 B/W Illustrations
ISBN 9781439838877 - CAT# K11767
Series: Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

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  • Describes the challenges that arise when designing classifiers for CAD systems
  • Includes both formal mathematical definitions and intuitive descriptions of the concepts
  • Presents state-of-the-art machine learning algorithms for CAD classifier design
  • Uses examples from real-life data, including statistical comparisons between methods
  • Provides useful and relevant references and publicly available code related to the areas explored in the text


Focusing on several recent, novel machine learning automatic algorithms, this reference provides the first source on the use of machine learning methods in designing computer-aided diagnosis (CAD) systems. It proposes a framework for CAD problems, presents the technical issues involved when building classifiers, and provides the appropriate machine learning techniques to address these problems. The book also includes results and concrete examples for different diseases and imaging modalities. It provides a useful tool for researchers and students in the biomedical sciences and machine learning as well as for advanced courses on CAD and/or medical informatics.