Consens, M.E.* ; Dufault, C.* ; Wainberg, M.* ; Forster, D.* ; Karimzadeh, M.* ; Goodarzi, H.* ; Theis, F.J. ; Moses, A.* ; Wang, B.*
Transformers and genome language models.
Nat. Mach. Intell., DOI: 10.1038/s42256-025-01007-9 (2025)
Richter, T. ; Bahrami, M. ; Xia, Y.* ; Fischer, D.S. ; Theis, F.J.
Delineating the effective use of self-supervised learning in single-cell genomics.
Nat. Mach. Intell., DOI: 10.1038/s42256-024-00934-3 (2025)
Schulze Buschoff, L.M. ; Akata, E. ; Bethge, M.* ; Schulz, E.
Visual cognition in multimodal large language models.
Nat. Mach. Intell. 7, 96-106 (2025)
Bak, M.* ; Madai, V.I.* ; Celi, L.A.* ; Kaissis, G. ; Cornet, R.* ; Maris, M.* ; Rueckert, D.* ; Buyx, A.* ; McLennan, S.*
Federated learning is not a cure-all for data ethics.
Nat. Mach. Intell. 6, 370–372 (2024)
Ziller, A.* ; Mueller, T.T.* ; Stieger, S. ; Feiner, L.F.* ; Brandt, J.* ; Braren, R.* ; Rueckert, D.* ; Kaissis, G.
Reconciling privacy and accuracy in AI for medical imaging.
Nat. Mach. Intell., DOI: 10.1038/s42256-024-00858-y (2024)
Debus, C.* ; Piraud, M. ; Streit, A.* ; Theis, F.J. ; Götz, M.*
Reporting electricity consumption is essential for sustainable AI.
Nat. Mach. Intell. 5, 1176-1178 (2023)
Dehner, C. ; Zahnd, G. ; Ntziachristos, V. ; Jüstel, D.
A deep neural network for real-time optoacoustic image reconstruction with adjustable speed of sound.
Nat. Mach. Intell. 5, 1130–1141 (2023)
Rädsch, T.* ; Reinke, A.* ; Weru, V.* ; Tizabi, M.D.* ; Schreck, N.* ; Kavur, A.E.* ; Pekdemir, B. ; Roß, T.* ; Kopp-Schneider, A.* ; Maier-Hein, L.*
Labelling instructions matter in biomedical image analysis.
Nat. Mach. Intell. 5, 273–283 (2023)
Bercea, C.-I. ; Wiestler, B.* ; Rueckert, D.* ; Albarqouni, S.
Federated disentangled representation learning for unsupervised brain anomaly detection.
Nat. Mach. Intell. 4, 685-695 (2022)
Schulte-Sasse, R.* ; Budach, S.* ; Hnisz, D.* ; Marsico, A.
Integration of multiomics data with graph convolutional networks to identify new cancer genes and their associated molecular mechanisms.
Nat. Mach. Intell. 3, 513–526 (2021)
Weiel, M.* ; Götz, M.* ; Klein, A.* ; Coquelin, D.* ; Floca, R.O.* ; Schug, A.*
Dynamic particle swarm optimization of biomolecular simulation parameters with flexible objective functions.
Nat. Mach. Intell., DOI: 10.1038/s42256-021-00366-3 (2021)
Holmberg, O. ; Köhler, N. ; Martins, T.* ; Siedlecki, J.* ; Herold, T.* ; Keidel, L.* ; Asani, B.* ; Schiefelbein, J.* ; Priglinger, S.* ; Kortuem, K.U.* ; Theis, F.J.
Self-supervised retinal thickness prediction enables deep learning from unlabelled data to boost classification of diabetic retinopathy.
Nat. Mach. Intell. 2, 719-726 (2020)
Matek, C. ; Schwarz, S.* ; Spiekermann, K.* ; Marr, C.
Human-level recognition of blast cells in acute myeloid leukemia with convolutional neural networks.
Nat. Mach. Intell. 1, 538-544 (2019)