PuSH - Publication Server of Helmholtz Zentrum München

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)
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.
Additional Metrics?
Edit extra informations Login
Publication type Article: Journal article
Document type Review
Keywords Open Science; Reproducibility; Guidelines; Bias
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
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)