Deep Learning in Cardiovascular Health: Sustainable Al Approaches for Heart Disease Diagnosis and Treatment: 77 - Rilegato

Rilegato

ISBN 10: 3032124697 ISBN 13: 9783032124692

Casa editrice: Springer-Verlag GmbH, 2026

Riassunto

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.

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Dalla quarta di copertina

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.

Dettagli dell'edizione

• Editore: Springer-Verlag GmbH
• Data di pubblicazione: 2026
• Lingua: Inglese
• ISBN 10: 3032124697
• ISBN 13: 9783032124692
• Rilegatura: Copertina rigida
• Numero di pagine: 276
• Redattore: Nag Anindya, Hassan Md. Mehedi, Bairagi Anupam Kumar
• Contatto del produttore: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Germania