Quantum Computing For Healthcare Data

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Quantum Computing for Healthcare Data

Quantum Computing for Healthcare Data: Revolutionizing the Future of Medicine presents an advanced overview of the fundamentals of quantum computing, from the transition of traditional to quantum computing, to the challenges and opportunities encountered as various industries enter into the paradigm shift. The book investigates how quantum AI, quantum data processing, and quantum data analysis can best be integrated into healthcare data systems. The book also introduces a range of case studies which feature applications of quantum computing in connected medical devices, medical simulations, robotics, medical diagnosis, and drug discovery. The book will be a valuable resource for researchers, graduate students, and professional programmers and computer engineers working in the areas of healthcare data management and analytics, blockchain, IoT, and big data analytics. - Explores the challenges and opportunities presented by quantum computing technology within healthcare data and applications - Compares quantum machine learning models and analyzes which offer the most promise for healthcare data analytics - Presents a range of case studies where quantum computing is starting to be applied, including connected medical devices, medical simulations, robotics, medical diagnosis, and drug discovery
Healthcare Analytics and Advanced Computational Intelligence

This book aims to apply state-of-the-art advanced computational intelligence frameworks in healthcare. It presents recent and real-life applications of computationally intelligent healthcare. It also discusses problems and solutions to remote healthcare and emergency healthcare services. Healthcare Analytics and Advanced Computational Intelligence highlights modern ambient intelligence-enabled healthcare models along with advanced topics like quantum computing in healthcare and cryptomedical systems. Healthcare Analytics and Advanced Computational Intelligence examines designing the latest medical systems and models that will allow the societal acceptance of ambiance computing in healthcare, medical imaging, health analytics, machine intelligence, sensory computing, medical data analytics, disease detection, telemedicine, and their applications. It includes diverse case studies dealing with various clinical-based applications. These intelligent models are primarily structured to deal with complex real-world issues in clinical data analytics, by means of state-of-the-art techniques with general implementation, domain-specific solutions, or hybrid methods which integrate computational intelligence with conventional statistical methods. The book is written for researchers and academicians in diverse areas. Engineers from technical disciplines such as computer engineering are likely to purchase the book. Various sub-streams such as machine learning, big data analytics, healthcare analytics, and computational intelligence will find the book significant for their curriculum.
Intelligent Technologies for Healthcare Business Applications

This book covers a wide range of applications and scenarios of intelligent technologies for healthcare business applications. The authors adopt an interdisciplinary approach with both theoretical and practical approaches in order to be relevant to multiple audiences. This book encapsulates fundamental and cutting-edge research paradigms of intelligent healthcare environments and addresses related open-ended research issues. The authors also explore recent advances, disseminate state-of-the-art techniques, and deploy novel technologies in intelligent healthcare services and applications. The book features a broad appeal to electrical, electronic, computer, software and telecommunications engineers in the healthcare space. Covers a range of applications and scenarios of intelligent technologies for healthcare business applications Explores advances, disseminates techniques, and deploys novel technologies in intelligent healthcare services Features paradigms of intelligent healthcare environments and addresses open-ended research issues