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2024 
The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data

Boulogne, LH, Lorenz, J, Kienzle, D, Schon, R, Ludwig, K, Lienhart, R, Jegou, S, Li, G, Chen, C, Wang, Q, Shi, D, Maniparambil, M, Muller, D, Mertes, S, Schroter, N, Hellmann, F, Elia, M, Dirks, I, Bossa, MN, Berenguer, AD, Mukherjee, T, Vandemeulebroucke, J, Sahli, H, Deligiannis, N, Gonidakis, P, Huynh, ND, Razzak, I, Bouadjenek, R, Verdicchio, M, Borrelli, P, Aiello, M, Meakin, JA, Lemm, A, Russ, C, Ionasec, R, Paragios, N, Ginneken, BV & Dubois, M-PR 2024, 'The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data', Medical Image Analysis, vol. 97, 103230. https://doi.org/10.1016/j.media.2024.103230, https://doi.org/10.48550/arXiv.2306.10484