Deep Learning in Cardiovascular Health
Sustainable Al Approaches for Heart Disease Diagnosis and Treatment
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Beschreibung
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.
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.
Highlights the use of different deep learning approaches in evaluating ECG signals, imaging data, patient health records Focuses on sustainable Al approaches for heart disease diagnosis and treatment Delves into different deep learning approaches, such as convolutional neural networks, recurrent neural networks
Autor*in
Anindya Nag
Themen in »Deep Learning in Cardiovascular Health«
Sustainable Deep Learning in Healthcare Deep Learning Cardiovascular Health Application Deep Learning Models for ECG Analysis Integrating AI into Cardiovascular Care Healthcare AI for Cardiovascular Diagnosis Advanced ML Techniques for Heart Health Deep Learning and Cardiovascular Wellness AI-enhanced Heart Disease Treatment Solutions