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Matschinske, J.* ; Alcaraz, N.* ; Benis, A.* ; Golebiewski, M.* ; Grimm, D.G.* ; Heumos, L. ; Kacprowski, T.* ; Lazareva, O.* ; List, M.* ; Louadi, Z.* ; Pauling, J.K.* ; Pfeifer, N.* ; Röttger, R.* ; Schwämmle, V.* ; Sturm, G.* ; Traverso, A.* ; van Steen, K.* ; de Freitas, M.V.* ; Villalba Silva, G.C.* ; Wee, L.* ; Wenke, N.K.* ; Zanin, M.* ; Zolotareva, O.* ; Baumbach, J.* ; Blumenthal, D.B.*

The AIMe registry for artificial intelligence in biomedical research.

Nat. Methods, DOI: 10.1038/s41592-021-01241-0 (2021)
DOI PMC
Open Access Green as soon as Postprint is submitted to ZB.
We present the AIMe registry, a community-driven reporting platform for AI in biomedicine. It aims to enhance the accessibility, reproducibility and usability of biomedical AI models, and allows future revisions by the community.
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Publication type Article: Journal article
Document type Review
Keywords Open Science; Reproducibility; Guidelines; Bias
Language english
Publication Year 2021
HGF-reported in Year 2021
ISSN (print) / ISBN 1548-7091
e-ISSN 1548-7105
Journal Nature Methods
Publisher Nature Publishing Group
Publishing Place New York, NY
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)
POF-Topic(s) 30205 - Bioengineering and Digital Health
Research field(s) Enabling and Novel Technologies
PSP Element(s) G-503800-001
Grants Ministry of Economy and Competitiveness | Agencia Estatal de Investigación (Spanish Agencia Estatal de Investigación)
Bayerisches Staatsministerium für Bildung und Kultus, Wissenschaft und Kunst (State Ministry of Education and Culture, Science and the Arts)
DOI 10.1038/s41592-021-01241-0
WOS ID WOS:000688389100001
Scopus ID 85113433776
PubMed ID 34433960
Erfassungsdatum 2021-10-01
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