Includes bibliographical references and index.

"In the last two decades, machine learning has been dramatically developed and is still experiencing a fast and ever-lasting change in paradigm, methodology, applications, and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on the diversity and complexity. Machine Learning Approaches and Applications Applied Intelligence for Healthcare Data Analytics presents a variety of techniques design to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design, along with interdisciplinary challenges. This book is useful to research scholars and students involved in critical condition analysis and computation models"--