Description
Computer-Assisted Diagnosis: Diabetes and Cardiovascular Disease brings together multifaceted information on research and clinical applications from an academic, clinical, bioengineering and bioinformatics perspective. The editors provide a stellar, diverse list of authors to explore this interesting field. Academic researchers, bioengineers, new investigators and students interested in diabetes and heart disease need an authoritative reference to reduce the amount of time spent on source-searching so they can spend more time on actual research and clinical application. This reference accomplishes this with contributions by authors from around the world.- Provides valuable information for academic clinicians, researchers, bioengineers and industry on diabetes and cardiovascular disease- Discusses the impact of diabetes on cardiovascular disease- Covers statistical classification techniques and risk stratification
Table of Contents
1. Cardiac Imaging: Clinical Principles and Applications2. Left Ventricle Segmentation for Cine MR Using Deep Learning3. Computational Methods for Identifying Left Ventricle Heart Pathologies4. Diabetes Mellitus and Atrial Fibrillation - Untying the Gordian Knot5. Carotenoids in Diabetes, Retinopathy, and Cardiovascular Risk6. Nanomedicine Approaches for the Diagnosis, Treatment, and Theragnosis of Diabetes Mellitus, Hypertension, and Their Associated Cardiovascular Disease7. Data-Driven Features Learning for Myocardial Registration and Segmentation8. Diabetes and Coronary Circulation: From Pathology to Imaging9. Prediction of Paravalvular Leak Post Transcatheter Aortic Valve Replacement10. Clinical Imaging Techniques for Assessing Vascular Risk and Complications in the Lower Extremities11. Management of Heart Failure in the Context of Type 2 Diabetes
