Machine Learning in Medicine

• Preface.- Introduction to Machine Learning Part Three.- Evolutionary Operations.- Multiple Treatments.- Multiple Endpoints.- Optimal Binning.- Exact P-Values.- Probit Regression.- Over - dispersion.10 Random Effects.- Weighted Least Squares.- Multiple Response Sets.- Complex Samples.- Runs Tests.- Decision Trees.- Spectral Plots.- Newton's Methods.- Stochastic Processes, Stationary Markov Chains.- Stochastic Processes, Absorbing Markov Chains.- Conjoint Models.- Machine Learning and Unsolved Questions.- Index.

From the reviews: "This book is excellent. It is valuable source of a basic understanding of novel machine learning methods of clinical data analysis and can be used as a reference by students and teachers of epidemiology, statistics and biostatistics, computer and social scientists, and clinical investigators." (Vedang J. Bhavsar, Doody's Book Reviews, March, 2014)