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This book provides a comprehensive overview of cutting-edge technologies in the diagnosis of multiple cardiovascular disease. Readers will understand technical advancements and research gaps, which will help them to optimize the design of algorithms and devices.
Cutting-Edge Diagnostic Technologies in Cardiovascular Diseases: Towards Data-Driven Smart Healthcare provides the details of adoption and implementation of advanced diagnostic techniques in different clinical settings including population screening, clinical diagnosis, risk prediction, data-driven diagnosis, and remote healthcare monitoring. It also covers various cardiovascular diseases from macrovascular to microvascular levels where early and accurate diagnosis is a high clinical need, e.g., stroke, intracranial atherosclerosis, coronary artery disease, coronary microvascular dysfunction, and peripheral artery disease. The book is a practical guide with case studies, and the authors cover a wide range of cutting-edge diagnostic techniques, including artificial intelligence, radiological imaging, computational fluid dynamics simulation, wearable sensors, genetic biomarkers, and data fusion. It summarizes the potentials, challenges, and research ethic concerns in the implementation under current clinical settings. It also discusses the future directions and prospectives for next-generation diagnostics based on AI-enhanced multimodal data fusion.
This book targets a mixed audience of data scientists, engineers, clinicians, researchers, academics, and students interested in cutting-edge technologies, methodologies, frameworks, and practices in the diagnostics of cardiovascular diseases to resolve the challenging gaps in healthcare and clinical applications.
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This book provides a comprehensive overview of cutting-edge technologies in the diagnosis of multiple cardiovascular disease. Readers will understand technical advancements and research gaps, which will help them to optimize the design of algorithms and devices.
Cutting-Edge Diagnostic Technologies in Cardiovascular Diseases: Towards Data-Driven Smart Healthcare provides the details of adoption and implementation of advanced diagnostic techniques in different clinical settings including population screening, clinical diagnosis, risk prediction, data-driven diagnosis, and remote healthcare monitoring. It also covers various cardiovascular diseases from macrovascular to microvascular levels where early and accurate diagnosis is a high clinical need, e.g., stroke, intracranial atherosclerosis, coronary artery disease, coronary microvascular dysfunction, and peripheral artery disease. The book is a practical guide with case studies, and the authors cover a wide range of cutting-edge diagnostic techniques, including artificial intelligence, radiological imaging, computational fluid dynamics simulation, wearable sensors, genetic biomarkers, and data fusion. It summarizes the potentials, challenges, and research ethic concerns in the implementation under current clinical settings. It also discusses the future directions and prospectives for next-generation diagnostics based on AI-enhanced multimodal data fusion.
This book targets a mixed audience of data scientists, engineers, clinicians, researchers, academics, and students interested in cutting-edge technologies, methodologies, frameworks, and practices in the diagnostics of cardiovascular diseases to resolve the challenging gaps in healthcare and clinical applications.