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Federated Deep Learning for Healthcare
Federated Deep Learning for Healthcare
A Practical Guide with Challenges and Opportunities
Contenu
This book provides a practical guide to federated deep learning for healthcare including fundamental concepts, framework, and the applications comprising of domain adaptation, model distillation, and transfer learning. It covers concerns in model fairness, data bias, regulatory compliance, and ethical dilemmas.
Informations bibliographiques
octobre 2024, 252 Pages, Advances in Smart Healthcare Technologies, Anglais
Taylor and Francis
978-1-03-268955-5
Sommaire
Mots-clés
Contenu
This book provides a practical guide to federated deep learning for healthcare including fundamental concepts, framework, and the applications comprising of domain adaptation, model distillation, and transfer learning. It covers concerns in model fairness, data bias, regulatory compliance, and ethical dilemmas.
Informations bibliographiques
octobre 2024, 252 Pages, Advances in Smart Healthcare Technologies, Anglais
Taylor and Francis
978-1-03-268955-5