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The STOIC2021 COVID-19 AI challenge: Applying reusable training methodologies to private data

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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 Revel
The STOIC2021 COVID-19 AI challenge: Applying reusable training methodologies to private data

History

Journal

Medical Image Analysis

Volume

97

Article number

103230

Pagination

1-17

Location

Amsterdam, The Netherlands

Open access

  • Yes

ISSN

1361-8415

eISSN

1361-8423

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

Publisher

Elsevier

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