Machine Learning in Health Care

How do you teach computers to learn from data? This hands-on introduction uses numerous realistic examples from the field of health care to convey the basics and the various methods of machine learning with R, H2O and Keras3. You will also learn how to prepare and visualize the data. Both statistical methods (such as regression, classification, factor, cluster methods) and neural networks are covered. In transfer learning with convolutional networks, heatmaps are used to show how results in image classification can be explained. Procedures and techniques in health care are subject to many regulations. This book explains what you need to do in order to achieve compliance. Key Features: Addresses the basic concepts and methods in machine learning so that you can get an idea of “what’s under the hood” Shows how to create packages and configure version control in R Shows how to create “tidy data” and visualize them with ggplot Shows ready-to-run, downloadable examples in health care with R, H2O and the actual version 3 of Keras Explains the steps needed to achieve compliance in an approval process