The AIMe registry for artificial intelligence in biomedical research

Julian Matschinske; Nicolas Alcaraz; Arriel Benis; Martin Golebiewski; Dominik G. Grimm; Lukas Heumos; Tim Kacprowski; Olga Lazareva; Markus List; Zakaria Louadi; Josch K. Pauling; Nico Pfeifer; Richard Röttger; Veit Schwämmle; Gregor Sturm; Alberto Traverso; Kristel Van Steen; Martiela Vaz de Freitas; Gerda Cristal Villalba Silva; Leonard Wee; Nina K. Wenke; Massimiliano Zanin; Olga Zolotareva; Jan Baumbach; David B. Blumenthal

doi:10.1038/s41592-021-01241-0

The AIMe registry for artificial intelligence in biomedical research

Julian Matschinske, Nicolas Alcaraz, Arriel Benis, Martin Golebiewski, Dominik G. Grimm, Lukas Heumos, Tim Kacprowski, Olga Lazareva, Markus List, Zakaria Louadi, Josch K. Pauling, Nico Pfeifer, Richard Röttger, Veit Schwämmle, Gregor Sturm, Alberto Traverso, Kristel Van Steen, Martiela Vaz de Freitas, Gerda Cristal Villalba Silva, Leonard WeeNina K. Wenke, Massimiliano Zanin, Olga Zolotareva, Jan Baumbach^*, David B. Blumenthal^*

^*Corresponding author for this work

Research output: Contribution to journal › Comment/debate › Research › peer-review

Original language	English
Journal	Nature Methods
Volume	18
Issue number	10
Pages (from-to)	1128–1131
ISSN	1548-7091
DOIs	https://doi.org/10.1038/s41592-021-01241-0
Publication status	Published - Oct 2021

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10.1038/s41592-021-01241-0

Cite this

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., ... Blumenthal, D. B. (2021). The AIMe registry for artificial intelligence in biomedical research. Nature Methods, 18(10), 1128–1131. https://doi.org/10.1038/s41592-021-01241-0

Matschinske, Julian ; Alcaraz, Nicolas ; Benis, Arriel ; Golebiewski, Martin ; Grimm, Dominik G. ; Heumos, Lukas ; Kacprowski, Tim ; Lazareva, Olga ; List, Markus ; Louadi, Zakaria ; Pauling, Josch K. ; Pfeifer, Nico ; Röttger, Richard ; Schwämmle, Veit ; Sturm, Gregor ; Traverso, Alberto ; Van Steen, Kristel ; de Freitas, Martiela Vaz ; Villalba Silva, Gerda Cristal ; Wee, Leonard ; Wenke, Nina K. ; Zanin, Massimiliano ; Zolotareva, Olga ; Baumbach, Jan ; Blumenthal, David B. / The AIMe registry for artificial intelligence in biomedical research. In: Nature Methods. 2021 ; Vol. 18, No. 10. pp. 1128–1131.

@article{252e731edde7470cafab66356015fe40,

title = "The AIMe registry for artificial intelligence in biomedical research",

author = "Julian Matschinske and Nicolas Alcaraz and Arriel Benis and Martin Golebiewski and Grimm, {Dominik G.} and Lukas Heumos and Tim Kacprowski and Olga Lazareva and Markus List and Zakaria Louadi and Pauling, {Josch K.} and Nico Pfeifer and Richard R{\"o}ttger and Veit Schw{\"a}mmle and Gregor Sturm and Alberto Traverso and {Van Steen}, Kristel and {de Freitas}, {Martiela Vaz} and {Villalba Silva}, {Gerda Cristal} and Leonard Wee and Wenke, {Nina K.} and Massimiliano Zanin and Olga Zolotareva and Jan Baumbach and Blumenthal, {David B.}",

note = "Funding Information: This project has received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreements No 826078 (R.R., J.M., N.K.W., J.B.) and No 777111 (T.K., J.B.). M.Z. received funding from the European Research Council (ERC) under the European Union{\textquoteright}s Horizon 2020 research and innovation programme (grant no. 851255). K.V.S. acknowledges funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under the Marie Sk{\l}odowska-Curie grant TranSYS (grant no. 860895). This publication reflects only the authors{\textquoteright} view, and the European Commission is not responsible for any use that may be made of the information it contains. J.B., T.K., M.L. and Z.L. were supported by the German Federal Ministry of Education and Research (BMBF) within the e:Med framework (J.B., T.K., M.L. and Z.L.: grant no. 01ZX1908A; J.B.: grant no. 01ZX1910D). J.B. and O.Z. were supported by the BMBF within the CLINSPECT-M framework (grant no. 031L0214A). A.B.{\textquoteright}s research is supported by a grant from Ariel University and Holon Institute of Technology, Israel: Applications of Artificial Intelligence for Enhancing the Efficiency of Vaccination Programs (grant no. RA19000000649). M.Z. acknowledges the Spanish State Research Agency, through the Severo Ochoa and Mar{\'i}a de Maeztu Program for Centers and Units of Excellence in R&D (grant no. MDM-2017-0711). M.V.d.F. and G.C.V.S. thank the Conselho Nacional de Desenvolvimento Cient{\'i}fico e Tecnol{\'o}gico (CNPq) for the fellowships provided (M.V.d.F.: process no. 140002/2018-9; G.C.V.S.: process no. 148615/2018-0). M.V.d.F. and G.C.V.S. also thank FIPE/HCPA for financial support. Contributions by J.K.P. and O.L. were funded by the Bavarian State Ministry of Science and the Arts within the framework coordinated by the Bavarian Research Institute for Digital Transformation (bidt; J.K.P.: Junior Research Group LipiTUM; O.L.: Doctoral Fellow). N.P. was supported by the DFG Cluster of Excellence Machine Learning – New Perspectives for Science (EXC 2064/1, project no. 390727645), by the BMBF (T{\"u}bingen AI Center, FKZ: 01IS18039A) and by the BMBF within the Medical Informatics Initiative (DIFUTURE, reference no. 01ZZ1804D).",

year = "2021",

month = oct,

doi = "10.1038/s41592-021-01241-0",

language = "English",

volume = "18",

pages = "1128–1131",

journal = "Nature Methods",

issn = "1548-7091",

publisher = "Nature Publishing Group",

number = "10",

}

Matschinske, J, Alcaraz, N, Benis, A, Golebiewski, M, Grimm, DG, Heumos, L, Kacprowski, T, Lazareva, O, List, M, Louadi, Z, Pauling, JK, Pfeifer, N, Röttger, R , Schwämmle, V, Sturm, G, Traverso, A, Van Steen, K, de Freitas, MV, Villalba Silva, GC, Wee, L, Wenke, NK, Zanin, M, Zolotareva, O, Baumbach, J & Blumenthal, DB 2021, 'The AIMe registry for artificial intelligence in biomedical research', Nature Methods, vol. 18, no. 10, pp. 1128–1131. https://doi.org/10.1038/s41592-021-01241-0

The AIMe registry for artificial intelligence in biomedical research. / Matschinske, Julian; Alcaraz, Nicolas; Benis, Arriel; Golebiewski, Martin; Grimm, Dominik G.; Heumos, Lukas; Kacprowski, Tim; Lazareva, Olga; List, Markus; Louadi, Zakaria; Pauling, Josch K.; Pfeifer, Nico; Röttger, Richard ; Schwämmle, Veit; Sturm, Gregor; Traverso, Alberto; Van Steen, Kristel; de Freitas, Martiela Vaz; Villalba Silva, Gerda Cristal; Wee, Leonard; Wenke, Nina K.; Zanin, Massimiliano; Zolotareva, Olga; Baumbach, Jan; Blumenthal, David B.

In: Nature Methods, Vol. 18, No. 10, 10.2021, p. 1128–1131.

Research output: Contribution to journal › Comment/debate › Research › peer-review

TY - JOUR

T1 - The AIMe registry for artificial intelligence in biomedical research

AU - Matschinske, Julian

AU - Alcaraz, Nicolas

AU - Benis, Arriel

AU - Golebiewski, Martin

AU - Grimm, Dominik G.

AU - Heumos, Lukas

AU - Kacprowski, Tim

AU - Lazareva, Olga

AU - List, Markus

AU - Louadi, Zakaria

AU - Pauling, Josch K.

AU - Pfeifer, Nico

AU - Röttger, Richard

AU - Schwämmle, Veit

AU - Sturm, Gregor

AU - Traverso, Alberto

AU - Van Steen, Kristel

AU - de Freitas, Martiela Vaz

AU - Villalba Silva, Gerda Cristal

AU - Wee, Leonard

AU - Wenke, Nina K.

AU - Zanin, Massimiliano

AU - Zolotareva, Olga

AU - Baumbach, Jan

AU - Blumenthal, David B.

N1 - Funding Information: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements No 826078 (R.R., J.M., N.K.W., J.B.) and No 777111 (T.K., J.B.). M.Z. received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant no. 851255). K.V.S. acknowledges funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant TranSYS (grant no. 860895). This publication reflects only the authors’ view, and the European Commission is not responsible for any use that may be made of the information it contains. J.B., T.K., M.L. and Z.L. were supported by the German Federal Ministry of Education and Research (BMBF) within the e:Med framework (J.B., T.K., M.L. and Z.L.: grant no. 01ZX1908A; J.B.: grant no. 01ZX1910D). J.B. and O.Z. were supported by the BMBF within the CLINSPECT-M framework (grant no. 031L0214A). A.B.’s research is supported by a grant from Ariel University and Holon Institute of Technology, Israel: Applications of Artificial Intelligence for Enhancing the Efficiency of Vaccination Programs (grant no. RA19000000649). M.Z. acknowledges the Spanish State Research Agency, through the Severo Ochoa and María de Maeztu Program for Centers and Units of Excellence in R&D (grant no. MDM-2017-0711). M.V.d.F. and G.C.V.S. thank the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for the fellowships provided (M.V.d.F.: process no. 140002/2018-9; G.C.V.S.: process no. 148615/2018-0). M.V.d.F. and G.C.V.S. also thank FIPE/HCPA for financial support. Contributions by J.K.P. and O.L. were funded by the Bavarian State Ministry of Science and the Arts within the framework coordinated by the Bavarian Research Institute for Digital Transformation (bidt; J.K.P.: Junior Research Group LipiTUM; O.L.: Doctoral Fellow). N.P. was supported by the DFG Cluster of Excellence Machine Learning – New Perspectives for Science (EXC 2064/1, project no. 390727645), by the BMBF (Tübingen AI Center, FKZ: 01IS18039A) and by the BMBF within the Medical Informatics Initiative (DIFUTURE, reference no. 01ZZ1804D).

PY - 2021/10

Y1 - 2021/10

U2 - 10.1038/s41592-021-01241-0

DO - 10.1038/s41592-021-01241-0

M3 - Comment/debate

C2 - 34433960

AN - SCOPUS:85113433776

VL - 18

SP - 1128

EP - 1131

JO - Nature Methods

JF - Nature Methods

SN - 1548-7091

IS - 10

ER -