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OverviewThis book showcases the most recent developments in the application of artificial intelligence to cardiology and medical imaging, with an emphasis on precise diagnosis, early prediction, and patient-centered care. In order to overcome clinical data ambiguity and enhance confidence in automated systems, it presents innovative frameworks that combine deep learning, fuzzy graph neural networks, metaheuristic optimization, and explainable AI. This book bridges the gap between state-of-the-art research and practical healthcare applications by covering a wide range of techniques, including CNNs, RNNs, residual networks, federated learning, and multimodal learning. As a research reference and a manual for implementing AI-driven healthcare solutions, it provides useful tools, datasets, and methodologies that foster innovation in precision medicine and medical decision-making. It is designed for researchers, clinicians, and students. Full Product DetailsAuthor: Anindya Nag , Md. Mehedi Hassan , Anupam Kumar BairagiPublisher: Springer Nature Switzerland AG Imprint: Springer Nature Switzerland AG ISBN: 9783032124692ISBN 10: 3032124697 Pages: 260 Publication Date: 26 May 2026 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Forthcoming Availability: Not yet available This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release. Table of ContentsIntroduction to Artificial Intelligence in Heart Disease Diagnostics.- Bridging Healthcare Gaps: Machine Learning Solutions for Cardiovascular Disease in Low Resource Settings.- Enhanced Cardiovascular Disease Prediction Using Machine Learning and Deep Learning Models with Optimized Feature Selection Techniques.- Effect of Metaheuristic Feature Selection Techniques for Cardiovascular Health.- FCVD ResNet An Interpretable Deep Residual Network for Cardiovascular Disease Risk Prediction.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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