This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research. "Big Data and Artificial Intelligence for Healthcare Applications" covers healthcare big data analytics, mobile health and personalized medicine, clinical trial data management and presents how Artificial Intelligence can be used for early disease diagnosis prediction and prognosis. It also offers some case studies that describes the application of Artificial Intelligence and Machine Learning in healthcare. Researchers, healthcare professionals, data scientists, systems engineers, students, programmers, clinicians, and policymakers will find this book of interest.

This work presents the latest development in the field of computational intelligence to advance Big Data and Cloud Computing concerning applications in medical diagnosis. As forum for academia and professionals it covers state-of-the-art research challenges and issues in the digital information & knowledge management and the concerns along with the solutions adopted in these fields.

There has been tremendous progress in cancer diagnosis and treatment methodologies, and this book focuses on major cancers of the cervix, breast, endometrium, and the associated reproductive system affecting women. It focuses on specific diagnostic techniques and treatment strategies including computational tools, Nanomedicine, and the use of Machine Learning (ML), Artificial Intelligence (AI), Big Data, and other latest techniques, including the evolution of these treatments over the years. Oncologists, cancer scientists, and professionals will find using the content on cutting-edge interventions by experts in their field, significantly improving earlier diagnosis and treatment options. Key Features: * Helps to improve quality of life after treatment as the focus of healthcare is shifting from curative methods to primary prevention of diseases, screening methods and early detection and treatment. * Appeals to clinicians and residents interested in exploring cutting-edge technology for early diagnoses and treatment of women associated cancers. * Features a chapter on the Clinician's perspective on advanced diagnostic and treatment methods.

This book reviews the application of artificial intelligence and machine learning in healthcare. It discusses integrating the principles of computer science, life science, and statistics incorporated into statistical models using existing data, discovering patterns in data to extract the information, and predicting the changes and diseases based on this data and models. The initial chapters of the book cover the practical applications of artificial intelligence for disease prognosis & management. Further, the role of artificial intelligence and machine learning is discussed with reference to specific diseases like diabetes mellitus, cancer, mycobacterium tuberculosis, and Covid-19. The chapters provide working examples on how different types of healthcare data can be used to develop models and predict diseases using machine learning and artificial intelligence. The book also touches upon precision medicine, personalized medicine, and transfer learning, with the real examples. Further, it also discusses the use of machine learning and artificial intelligence for visualization, prediction, detection, and diagnosis of Covid -19. This book is a valuable source of information for programmers, healthcare professionals, and researchers interested in understanding the applications of artificial intelligence and machine learning in healthcare.