Federated Deep Learning for Healthcare

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.

Aceasta carte ofera un ghid practic pentru invatarea profunda federata pentru asistenta medicala, inclusiv concepte fundamentale, cadrul si aplicatiile care includ adaptarea domeniului, distilarea modelului si invatarea prin transfer. Acesta acopera preocuparile privind corectitudinea modelului, partinirea datelor, conformitatea cu reglementarile si dilemele etice.