Understanding the eye through data — from single synapses to population-scale disease.
01
Köhler, P., Fadugba, J., Berens, P., Koch, L.M.
Efficiently correcting patch-based segmentation errors to control image-level performance in retinal images
02
Wundram, A.M., Fischer, P., Wunderlich, S., Faber, H., Koch, L.M., Berens, P., Baumgartner C. F.
Leveraging Probabilistic Segmentation Models for Improved Glaucoma Diagnosis: A Clinical Pipeline Approach
03
Yaïci, R., Cieplucha, M., Bock, R. et al
ChatGPT und die deutsche Facharztprüfung für Augenheilkunde: eine Evaluierung
04
Koch, L.M., Baumgartner, C.F. & Berens, P
Distribution shift detection for the postmarket surveillance of medical AI algorithms: a retrospective simulation study
05
Ayhan, M. S., Neubauer, J., Uzel, M. M., Gelisken, F., & Berens, P.
Interpretable detection of epiretinal membrane from optical coherence tomography with deep neural networks.
06
González-Márquez, R., Schmidt, L., Schmidt, B. M., Berens, P., & Kobak, D.
The landscape of biomedical research
07
Grote, T., Berens, P.
A paradigm shift?—On the ethics of medical large language models
08
Sun, S., Koch, L. M., & Baumgartner, C. F.
Right for the Wrong Reason: Can Interpretable ML Techniques Detect Spurious Correlations?
09
Ayhan, M. S., Faber, H., Kühlewein, L., Inhoffen, W., Aliyeva, G., Ziemssen, F., & Berens, P.
Multitask Learning for Activity Detection in Neovascular Age-Related Macular Degeneration
10
Djoumessi, K. R. D., Ilanchezian, I., Kühlewein, L., Faber, H., Baumgartner, C. F., Bah, B., Berens, P. & Koch, L. M.
Sparse Activations for Interpretable Disease Grading
11
Sun, S., Woerner, S., Maier, A., Koch, L.M., Baumgartner,, C.F.
Inherently Interpretable Multi-Label Classification Using Class-Specific Counterfactuals
12
Grote, T., & Berens, P
Uncertainty, evidence, and the integration of machine learning into medical practice
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Congiu, M., Mondoloni, S., Zouridis, I. S., Schmors, L., Lecca, S., Lalive, A. L., Ginggen, K., Deng, F., Berens, P., Paolicelli, R. C., Li, Y., Burgalossi, A. & Mameli, M.
Plasticity of neuronal dynamics in the lateral habenula for cue-punishment associative learning
14
Böhm, J. N., Berens, P., & Kobak, D.
Unsupervised visualization of image datasets using contrastive learning
15
Damrich, S., Böhm, J. N., Hamprecht, F. A., & Kobak, D.
From t-SNE to UMAP with contrastive learning
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Bachmann, F., Hennig, P., Kobak, D.