"Technology today is revolutionizing everything with the healthcare domain also seeing a major move towards automation. Intelligent systems assist doctors in diagnosing and giving prognosis with good accuracy and at a large scale. This new book, Data-Driven Analytics for Healthcare: Artificial Intelligence and Machine Learning for Medical Diagnostics, provides insight into various solutions for the diagnosis of patients with the help of automated processes using artificial intelligence techniques and technology. This book highlights the possibilities of artificial intelligence, machine learning, and deep learning techniques and various tools to correctly diagnose various medical problems. It explores the opportunities in the data-driven analytics for healthcare in terms of research conducted in this domain and how the data in various healthcare-related applications can be handled and used. General predictive analysis methods are explained in various disease detection applications along with machine learning techniques for the implementation of predictive analysis methods. How the human brain can be used as a quantum computer for biomimetics and the mind-machine interface are also explained. The book covers object detection approaches for diseases such as pneumonia, application of monitoring and tracking the coronavirus disease, various endodontic applications for handling diagnostic abnormalities using deep learning methods, and applications of healthcare for human activity recognition in detail. It also studies the applications of artificial intelligence and machine learning for various medical applications, including MRI, X-ray, CT scan images and diagnosis, patient history data for diseases prediction, prescription of various drugs, and more. This book will be of interest to computer scientists, electronics engineers, and bioinformatics researchers, pharmaceuticals professionals, and medical doctors, biotech professionals, and others in understanding the use and adoption of artificial intelligence and machine learning in healthcare and medicine"--