Cutting-Edge Diagnostic Technologies in Cardiovascular Diseases
CRC Press (Verlag)
978-1-032-77169-4 (ISBN)
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.
Haipeng Liu received his Bachelor and Master in Engineering degrees from Zhejiang University, China, in 2012 and 2015, respectively, and Doctor of Philosophy in Medical Sciences from the Chinese University of Hong Kong, in 2018. From 2019 to 2024, he was a research fellow in Anglia Ruskin University and Coventry University, UK. He is currently an assistant professor at Coventry University. He is the author of over 90 journal articles, 11 conference papers, and 23 book chapters. Dr Liu is an editor of four academic books and seven special issues, and an editorial member of four scientific journals. His research interests include biomechanics, physiological measurement, and computational simulation of cardiovascular diseases. Dr. Liu was a recipient of two Travel Awards of British Heart Foundation, the Research and Innovation Support Fund of Anglia Ruskin University, and the Official Development Assistance (ODA) Fund of Coventry University. Gary Tse completed his pre-clinical training at Trinity Hall, Cambridge (2008), and was subsequently awarded a Doctor of Philosophy (Ph.D.) degree in Cardiac Electrophysiology (2015) and a Doctor of Medicine (M.D.) degree in Cardiovascular Epidemiology (2022) from the University of Cambridge. He was elected a fellow of the European Society of Cardiology (2016), American College of Cardiology (2017), Heart Rhythm Society (2018), Royal College of Physicians of London (2019), Royal College of Paediatrics and Child Health (2019), and Royal College of Pathologists (2022). Currently, he leads a team of researchers from China (Tianjin, Hong Kong) and the UK (Kent, Surrey, and London) focusing on the use of big data for cardiovascular risk prediction. He serves on the Council of the International Society of Electrocardiology, for which he is currently the Secretary. He is a Board of Trustees member of the International Society for Noninvasive Electrocardiology and a Nucleus Committee member of the Population Health Section, European Association of Preventive Cardiology.
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
| Erscheinungsdatum | 17.05.2025 |
|---|---|
| Zusatzinfo | 20 Tables, black and white; 18 Line drawings, black and white; 26 Halftones, black and white; 44 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 690 g |
| Themenwelt | Medizinische Fachgebiete ► Innere Medizin ► Kardiologie / Angiologie |
| Medizin / Pharmazie ► Medizinische Fachgebiete ► Radiologie / Bildgebende Verfahren | |
| Medizin / Pharmazie ► Physiotherapie / Ergotherapie ► Orthopädie | |
| Technik ► Medizintechnik | |
| ISBN-10 | 1-032-77169-0 / 1032771690 |
| ISBN-13 | 978-1-032-77169-4 / 9781032771694 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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