Quantum Computing and Intelligence for Smart Healthcare Systems

The rapid evolution of healthcare in the digital era has created a growing demand for intelligent, secure technologies capable of addressing increasingly complex clinical and operational challenges. As traditional computing approaches face limitations in processing the scale, complexity, and real-time demands of modern healthcare data, quantum computing offers a transformative alternative. Leveraging principles such as superposition and entanglement, quantum systems have the potential to solve optimization, simulation, and data-processing problems that are difficult or impossible for classical computers. At the same time, artificial intelligence (AI) is reshaping healthcare through applications in disease prediction, medical imaging, clinical decision support, and personalized medicine. The convergence of quantum computing and AI presents new opportunities to accelerate data analysis, enhance predictive capabilities, strengthen cybersecurity, and improve healthcare outcomes. As smart healthcare systems increasingly rely on continuous monitoring, connected medical devices, and real-time data exchange, advances in quantum technologies may also support more secure communication and privacy protection. Realizing these benefits, however, requires careful consideration of ethical, technical, and regulatory challenges surrounding healthcare data and emerging technologies. Quantum Computing and Intelligence for Smart Healthcare Systems examines the intersection of quantum computing, AI, and smart healthcare technologies, bridging foundational theory with practical applications in modern healthcare environments. This book explores how quantum-enabled approaches can address challenges related to computational scalability, large-scale data analytics, personalized medicine, and secure health information management. Covering topics such as big data processing, personalized medicine, and smart hospitals, this book serves as a valuable resource for graduate and doctoral students, machine learning practitioners, healthcare technology developers, data security specialists, policymakers, researchers, and academics interested in the future of intelligent healthcare systems.