The application of machine learning is growing exponentially into every branch of business and science, including medical sciences. This book presents the integration of machine learning (ML) and deep learning (DL) algorithms that can be applied in healthcare sector to reduce the time needed by doctors, radiologists, and a other medical professionals to analyze, predict, and diagnose conditions with accurate results. The book offers important key aspects in the development and the implementation of ML and DL approaches towards developing prediction tools and models and improving medical diagnosis. The contributors explore recent trends innovations, challenges, and solutions, as well as case studies of the applications of ML and DL in intelligent system-based disease diagnosis. The chapters also highlight the basics and the need for applying mathematical aspects with reference to the development of new medical models. The authors also explore ML and DL in relation to AI prediction tools, the discovery of drugs, neuroscience, and diagnosis in multiple imaging modalities. They also explore pattern recognition approaches to functional magnetic resonance imaging (FMRI) images. This book is for students and researchers of computer science and engineering, electronics and communication engineering, information technology, biomedical engineering researchers, academicians, educators, and in other areas of the healthcare sector.