Full Description
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 details on the 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 the macrovascular to microvascular levels, where early and accurate diagnosis is a high clinical need, for example, stroke, intracranial atherosclerosis, coronary artery disease, and microvascular dysfunction. 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, wearable sensors, genetic biomarkers, and multi-omics data integration. It summarizes the potentials, challenges, and ethical concerns in the implementation of these techniques under current clinical settings. It also discusses the future directions and perspectives 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, and practices in the diagnostics of cardiovascular diseases to resolve the challenging gaps in healthcare and clinical applications.
Contents
Chapter 1- Novel Approaches in Cardiovascular Diagnostics: Mapping the Research Landscape of the 21st Century
Chapter 2- Cardiovascular Disease Detection and Monitoring Using Wearable Devices and Machine Learning
Chapter 3- Wearable electrocardiogram sensors for home monitoring of cardiovascular diseases
Chapter 4- Application of Electroencephalogram in Detecting Cerebral Small Vessel Disease
Chapter 5- Neuroimaging Biomarkers in Diagnosing Cerebral Small Vessel Disease
Chapter 6- Role of Plasma Inflammatory and Blood biomarkers in CSVD
Chapter 7- Model-Driven Prediction of Blood Pressure Leveraging Multimodal Sensing Data
Chapter 8- Enhancing Cardiorespiratory and vascular assessment through enhancement of the PPG Signal: USPPG Signal Analysis
Chapter 9- Enhanced diagnosis of myocardial ischemia via advanced cardiac imaging techniques and AI-based ECG-derived approaches
Chapter 10- Investigating the Relationship Between Myocardial Parameters and Coronary Microvascular Dysfunction (CMD): A Focus on Ischemia
Chapter 11- Integrating Advanced Sensing Technologies and AI for Predicting Cardiovascular Risks: A Data-Driven Approach in Modern Healthcare
Chapter 12- Application of Artificial Intelligence in Coronary Computed Tomography Angiography: Progress and Challenges
Chapter 13- Diagnosis and Treatment of Acute Ischemic Stroke Using Modern Neuroimaging and Artificial Intelligence
Chapter 14- Mass Spectrometry Based Multi-Omic Approaches to Discover Biomarkers for Coronary Artery Diseases
