id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
bracis-33555	Negrão, Arthur; Silva, Guilherme; Pedrosa, Rodrigo; Luz, Eduardo; Silva, Pedro	Adaptive Client-Dropping in Federated Learning: Preserving Data Integrity in Medical Domains	2024		.htm	text/html	6098	311	48	These results demonstrate that the proposed strategy is resilient against corrupted data and does not negatively impact scenarios without corrupted clients. Specially on cases where accuracy drops are mild, where the high uncertainty on corrupted client predictions would probably be masked, those metrics can provide good intel whether a client is corrupted or not.	cache/bracis-33555.htm	txt/bracis-33555.txt