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Overview: This book is a comprehensive review of technologies and data in healthcare services. It features a compilation of 10 chapters that inform readers about the recent research and developments in this field. Each chapter focuses on a specific aspect of healthcare services, highlighting the potential impact of technology on enhancing practices and outcomes. The main features of the book include 1) referenced contributions from healthcare and data analytics experts, 2) a broad range of topics that cover healthcare services, and 3) demonstration of Deep Learning techniques for specific diseases. This book invited ideas, proposals, review articles and experimental works from the researchers working in the field. The systematic organization of the research works in the field of applying Machine Learning for disease prediction will be fruitful in providing insights to readers about the existing works and the gaps available in the field. This book is a significant contribution towards providing a detailed study of data analytics algorithms and Machine Learning techniques for disease prediction. The book includes a rigorous review of related literature, methodology for data set preparation, model building, training, and testing the model. It contains a comparative analysis of versatile algorithms applied for making predictions in the challenging arena of medical science and disease prediction. The provides good insight into the topics such as Data Analytics, Machine Learning, Deep Learning, Information Retrieval from medical data, Data Integration, Prediction Models, Medical Data Analysis, Medical Decision Support systems, Federated Learning in Healthcare, and Medical Image Reconstruction. The book is a companion and a must-read, for academicians, people from industries, graduate and post-graduate students, researchers, physicians and for everyone who is involved in the fields of medicine, Data Analytics or Machine Learning directly or indirectly.
Genre: Non-Fiction > Tech & Devices
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