| 2025 | ICML | EEG-Language Pretraining for Highly Label-Efficient Clinical Phenotyping. | Sam Gijsen, Kerstin Ritter |
| 2024 | EDBT | TLIMB - A Transfer Learning Framework for IMage Analysis of the Brain. | Marc-Andre Schulz, Jan Philipp Albrecht, Alpay Yilmaz, Alexander Koch, Dagmar Kainmller, Ulf Leser, Kerstin Ritter |
| 2024 | MICCAI | DeepRepViz: Identifying Potential Confounders in Deep Learning Model Predictions. | Roshan Prakash Rane, JiHoon Kim, Arjun Umesha, Didem Stark, Marc-Andr Schulz, Kerstin Ritter |
| 2022 | MICCAI | Data Augmentation via Partial Nonlinear Registration for Brain-Age Prediction. | Marc-Andre Schulz, Alexander Koch, Vanessa Emanuela Guarino, Dagmar Kainmueller, Kerstin Ritter |
| 2021 | MICCAI | MRI Image Registration Considerably Improves CNN-Based Disease Classification. | Malte Klingenberg, Didem Stark, Fabian Eitel, Kerstin Ritter |
| 2019 | MICCAI | Testing the Robustness of Attribution Methods for Convolutional Neural Networks in MRI-Based Alzheimer's Disease Classification. | Fabian Eitel, Kerstin Ritter |
| 2019 | MICCAI | Predicting Fluid Intelligence in Adolescent Brain MRI Data: An Ensemble Approach. | Shikhar Srivastava, Fabian Eitel, Kerstin Ritter |
| 2018 | MICCAI | Visualizing Convolutional Networks for MRI-Based Diagnosis of Alzheimer's Disease. | Johannes Rieke, Fabian Eitel, Martin Weygandt, John-Dylan Haynes, Kerstin Ritter |