A cautionary tale on the cost-effectiveness of collaborative AI in real-world medical applications
Lucia Innocenti,
Sebastien Ourselin,
Vicky Goh
et al.
Abstract:Federated learning (FL) has gained wide popularity as a collaborative learning paradigm enabling trustworthy AI in sensitive healthcare applications. Never-theless, the practical implementation of FL presents technical and organizational challenges, as it generally requires complex communication infrastructures. In this context, consensus-based learning (CBL) may represent a promising collaborative learning alternative, thanks to the ability of combining local knowledge into a federated decision system, while … Show more
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