LITMIR.BIZ

      Preface

      Computational intelligence (CI) refers to the ability of computers to accomplish tasks that are normally completed by intelligent beings such as humans and animals. With the rapid advance of technology, artificial intelligence (AI) techniques are being effectively used in the fields of health to improve the efficiency of treatments, avoid the risk of false diagnoses, make therapeutic decisions, and predict the outcome in many clinical scenarios. Modern health treatments are faced with the challenge of acquiring, analysing and applying the large amount of knowledge necessary to solve complex problems. Computational intelligence in healthcare mainly uses computer techniques to perform clinical diagnoses and suggest treatments. In the present scenario of computing, CI tools present adaptive mechanisms that permit the understanding of data in difficult and changing environments. The desired results of CI technologies profit medical fields by assembling patients with the same types of diseases or fitness problems so that healthcare facilities can provide effectual treatments.

      This book starts with the fundamentals of computer intelligence and the techniques and procedures associated with it. Contained in this book are state-of-the-art methods of computational intelligence and other allied techniques used in the healthcare system, as well as advances in different CI methods that will confront the problem of effective data analysis and storage faced by healthcare institutions. The objective of this book is to provide researchers with a platform encompassing state-of-the-art innovations; research and design; implementation of methodological and algorithmic solutions to data processing problems; and the design and analysis of evolving trends in health informatics, intelligent disease prediction and computer-aided diagnosis.

      The book aims to integrate several aspects of CI, like machine learning and deep learning, from diversified perspectives involving recent research trends and advanced topics in the field which will be of interest to academicians and researchers working in this area. The purpose of the book is to endow different communities with innovative advances in theory, analytical approaches, numerical simulation, statistical analysis, modeling, advanced deployment, case studies, analytical results, computational structuring and significance progress in the field of machine learning and deep learning in healthcare applications. This book is targeted towards scientists, application doctors, health professionals, professors, researchers and students. Different dimensions of CI applications will be revealed and its use as a solution for assorted real-world biomedical and healthcare problems is illustrated. Following is a brief description of the subjects covered in each chapter.