Deep Learning in Cardiovascular Health: Sustainable Al Approaches for Heart Disease Diagnosis and Treatment

Author:   Anindya Nag ,  Md. Mehedi Hassan ,  Anupam Kumar Bairagi
Publisher:   Springer Nature Switzerland AG
ISBN:  

9783032124692


Pages:   260
Publication Date:   26 May 2026
Format:   Hardback
Availability:   Not yet available   Availability explained
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Deep Learning in Cardiovascular Health: Sustainable Al Approaches for Heart Disease Diagnosis and Treatment


Overview

This 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 Details

Author:   Anindya Nag ,  Md. Mehedi Hassan ,  Anupam Kumar Bairagi
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
ISBN:  

9783032124692


ISBN 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   Availability explained
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 Contents

Introduction 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.

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