id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
cord-159103-dbgs2ado	Rieke, Nicola	The Future of Digital Health with Federated Learning	2020-03-18		.txt	text/plain	6704	264	41	Medical data is particularly diverse -not only in terms of type, dimensionality and characteristics of medical data in general but also within a defined medical task, due to factors like acquisition protocol, brand of the medical device or local demographics. key: cord-159103-dbgs2ado authors: Rieke, Nicola; Hancox, Jonny; Li, Wenqi; Milletari, Fausto; Roth, Holger; Albarqouni, Shadi; Bakas, Spyridon; Galtier, Mathieu N.; Landman, Bennett; Maier-Hein, Klaus; Ourselin, Sebastien; Sheller, Micah; Summers, Ronald M.; Trask, Andrew; Xu, Daguang; Baust, Maximilian; Cardoso, M. Jorge title: The Future of Digital Health with Federated Learning date: 2020-03-18 journal: nan DOI: nan sha: doc_id: 159103 cord_uid: dbgs2ado Data-driven Machine Learning has emerged as a promising approach for building accurate and robust statistical models from medical data, which is collected in huge volumes by modern healthcare systems.	cache/cord-159103-dbgs2ado.txt	txt/cord-159103-dbgs2ado.txt
