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This book examines the use of biomedical signal processing in analyzing and diagnosing various medical conditions, particularly diseases related to the heart and brain. In combination with machine learning tools and other optimization methods, analysis of biomedical signals improves patient outcomes through early, reliable detection.

This book provides a proficient guide on the relationship between AI and healthcare and how AI is changing all aspects of the health care industry. It also covers how deep learning will help in diagnosis and prediction of disease spread.

This book describes the fundamental concepts of machine learning and deep learning techniques in a healthcare system. The aim of this book is to describe how deep learning methods are used to insure high quality data processing, medical image and signal analysis, and improved healthcare application.

This book covers recent research on the COVID-19 pandemic. It includes the analysis, implementation, usage, and proposed ideas and models with architecture to handle the COVID-19 outbreak. Using advanced technologies such as artificial intelligence (AI) and machine learning (ML), techniques for data analysis, this book will be helpful to mitigate exposure and ensure public health. We know prevention is better than cure, so by using several ML techniques, researchers can try to predict the disease in its early stage and develop more effective medications and treatments. Computational technologies in areas like AI, ML, Internet of Things (IoT), and drone technologies underlie a range of applications that can be developed and utilized for this purpose. Because in most cases there is no one solution to stop the spreading of pandemic diseases, and the integration of several tools and tactics are needed. Many successful applications of AI, ML, IoT, and drone technologies already exist, including systems that analyze past data to predict and conclude some useful information for controlling the spread of COVID-19 infections using minimum resources. The AI and ML approach can be helpful to design different models to give a predictive solution for mitigating infection and preventing larger outbreaks. This book:Examines the use of artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), and drone technologies as a helpful predictive solution for controlling infection of COVID-19Covers recent research related to the COVID-19 pandemic and includes the analysis, implementation, usage, and proposed ideas and models with architecture to handle a pandemic outbreakExamines the performance, implementation, architecture, and techniques of different analytical and statistical models related to COVID-19Includes different case studies on COVID-19Dr. Chhabi Rani Panigrahi is Assistant Professor in the Department of Computer Science at Rama Devi Women's University, Bhubaneswar, India.Dr. Bibudhendu Pati is Associate Professor and Head of the Department of Computer Science at Rama Devi Women's University, Bhubaneswar, India.Dr. Mamata Rath is Assistant Professor in the School of Management (Information Technology) at Birla Global University, Bhubaneswar, India.Prof. Rajkumar Buyya is a Redmond Barry Distinguished Professor and Director of the Cloud Computing and Distributed Systems (CLOUDS) Laboratory at the University of Melbourne, Australia.