The STOIC2021 COVID-19 AI challenge: Applying reusable training methodologies to private data
journal contribution
posted on 2024-07-04, 02:33 authored by Luuk H Boulogne, Julian Lorenz, Daniel Kienzle, Robin Schön, Katja Ludwig, Rainer Lienhart, Simon Jégou, Guang Li, Cong Chen, Qi Wang, Derik Shi, Mayug Maniparambil, Dominik Müller, Silvan Mertes, Niklas Schröter, Fabio Hellmann, Miriam Elia, Ine Dirks, Matías Nicolás Bossa, Abel Díaz Berenguer, Tanmoy Mukherjee, Jef Vandemeulebroucke, Hichem Sahli, Nikos Deligiannis, Panagiotis Gonidakis, Ngoc Dung Huynh, Imran RazzakImran Razzak, Mohamed Reda BouadjenekMohamed Reda Bouadjenek, Mario Verdicchio, Pasquale Borrelli, Marco Aiello, James A Meakin, Alexander Lemm, Christoph Russ, Razvan Ionasec, Nikos Paragios, Bram van Ginneken, Marie-Pierre RevelThe STOIC2021 COVID-19 AI challenge: Applying reusable training methodologies to private data
History
Journal
Medical Image AnalysisVolume
97Article number
103230Pagination
1-17Location
Amsterdam, The NetherlandsPublisher DOI
Open access
- Yes
ISSN
1361-8415eISSN
1361-8423Language
engPublication classification
C1.1 Refereed article in a scholarly journalPublisher
ElsevierPublication URL
Usage metrics
Licence
Exports
RefWorksRefWorks
BibTeXBibTeX
Ref. managerRef. manager
EndnoteEndnote
DataCiteDataCite
NLMNLM
DCDC