| 2025 | MICCAI | Simulating Inter-observer Variability Across Clinical Experience Levels for Brain Tumour Segmentation. | Haley Gillett, Emma A. M. Stanley, Raissa Souza, Matthias Wilms, Nils D. Forkert |
| 2025 | MICCAI | Exploring the Interplay of Label Bias with Subgroup Size and Separability: A Case Study in Mammographic Density Classification. | Emma A. M. Stanley, Raghav Mehta, Mlanie Roschewitz, Nils D. Forkert, Ben Glocker |
| 2025 | MICCAI | Synthetic Ground Truth Counterfactuals for Comprehensive Evaluation of Causal Generative Models in Medical Imaging. | Emma A. M. Stanley, Vibujithan Vigneshwaran, Erik Y. Ohara, Finn G. Vamosi, Nils D. Forkert, Matthias Wilms |
| 2024 | MICCAI | Do Sites Benefit Equally from Distributed Learning in Medical Image Analysis? | Raissa Souza, Emma A. M. Stanley, Richard Camicioli, Oury Monchi, Zahinoor Ismail, Matthias Wilms, Nils D. Forkert |
| 2024 | MICCAI | Assessing the Impact of Sociotechnical Harms in AI-Based Medical Image Analysis. | Emma A. M. Stanley, Raissa Souza, Anthony J. Winder, Matthias Wilms, G. Bruce Pike, Gabrielle Dagasso, Christopher Nielsen, Sarah J. MacEachern, Nils D. Forkert |
| 2024 | MICCAI | A Lightweight 3D Conditional Diffusion Model for Self-explainable Brain Age Prediction in Adults and Children. | Matthias Wilms, Ahmad O. Ahsan, Erik Y. Ohara, Gabrielle Dagasso, Elizabeth Macavoy, Emma A. M. Stanley, Vibujithan Vigneshwaran, Nils D. Forkert |
| 2023 | MICCAI | A Flexible Framework for Simulating and Evaluating Biases in Deep Learning-Based Medical Image Analysis. | Emma A. M. Stanley, Matthias Wilms, Nils D. Forkert |
| 2022 | MICCAI | Disproportionate Subgroup Impacts and Other Challenges of Fairness in Artificial Intelligence for Medical Image Analysis. | Emma A. M. Stanley, Matthias Wilms, Nils D. Forkert |