This book explores one of the most transformative shifts in modern medicine—the emergence of digital twins and their potential to redefine how diseases are understood, predicted, and treated. By integrating advances in artificial intelligence, systems biology, computational modeling, and personalized medicine, this book presents a comprehensive perspective on how virtual representations of the human body can enable predictive, preventive, and precision healthcare. The book highlights the scientific foundations and technological innovations driving the development of digital twins in healthcare. It examines how patient-specific computational models can simulate physiological processes, predict disease progression, and optimize therapeutic strategies before they are applied in real life. Applications discussed include drug discovery, personalized treatment planning, clinical decision support, remote patient monitoring, and the creation of virtual clinical trials that can significantly accelerate biomedical innovation. Structured to bridge theory and application, the book introduces core concepts of digital twin technology, explores current research and emerging platforms, and discusses ethical, regulatory, and clinical implications of implementing virtual healthcare systems. This book will be valuable for researchers, clinicians, biomedical engineers, data scientists, and healthcare innovators interested in the future of computational medicine, personalized healthcare, and next-generation medical technologies.
