@article{roschewitz2023automatic,title={Automatic correction of performance drift under acquisition shift in medical image classification},author={Roschewitz, M{\'e}lanie and Khara, Galvin and Yearsley, Joe and Sharma, Nisha and James, Jonathan J and Ambr{\'o}zay, {\'E}va and Heroux, Adam and Kecskemethy, Peter and Rijken, Tobias and Glocker, Ben},journal={Nature Communications},volume={14},number={1},pages={6608},year={2023},month=oct,publisher={Nature Publishing Group UK London},selected=true,}
@inproceedings{roschewitz2023distance,title={Distance Matters For Improving Performance Estimation Under Covariate Shift},author={Roschewitz, M{\'e}lanie and Glocker, Ben},booktitle={2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)},pages={4551--4561},year={2023},organization={IEEE},}
@article{glocker2023algorithmic,title={Algorithmic encoding of protected characteristics in chest X-ray disease detection models},author={Glocker, Ben and Jones, Charles and Bernhardt, M{\'e}lanie and Winzeck, Stefan},journal={Ebiomedicine},volume={89},year={2023},publisher={Elsevier},month=feb,}
@inproceedings{jones2023role,title={The role of subgroup separability in group-fair medical image classification},author={Jones, Charles and Roschewitz, M{\'e}lanie and Glocker, Ben},booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)},pages={179--188},year={2023},organization={Springer},}
@inproceedings{rosnati2023robust,title={Robust semi-supervised segmentation with timestep ensembling diffusion models},author={Rosnati, Margherita and Roschewitz, M{\'e}lanie and Glocker, Ben},booktitle={Machine Learning for Health (ML4H)},pages={512--527},year={2023},organization={PMLR},}
@article{glocker2023risk,title={Risk of bias in chest radiography deep learning foundation models},author={Glocker, Ben and Jones, Charles and Roschewitz, M{\'e}lanie and Winzeck, Stefan},journal={Radiology: Artificial Intelligence},volume={5},number={6},pages={e230060},month=sep,year={2023},publisher={Radiological Society of North America},}
@article{bernhardt2022active,title={Active label cleaning for improved dataset quality under resource constraints},author={Bernhardt, M{\'e}lanie and Castro, Daniel C and Tanno, Ryutaro and Schwaighofer, Anton and Tezcan, Kerem C and Monteiro, Miguel and Bannur, Shruthi and Lungren, Matthew P and Nori, Aditya and Glocker, Ben and others},journal={Nature communications},volume={13},number={1},pages={1161},year={2022},month=mar,publisher={Nature Publishing Group UK London},selected=true,}
@article{bernhardt2022potential,title={Potential sources of dataset bias complicate investigation of underdiagnosis by machine learning algorithms},author={Bernhardt, M{\'e}lanie and Jones, Charles and Glocker, Ben},journal={Nature Medicine},volume={28},number={6},pages={1157--1158},year={2022},publisher={Nature Publishing Group US New York},selected=true}
@article{bernhardt2022failure,title={Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed},author={Bernhardt, M{\'e}lanie and Ribeiro, Fabio De Sousa and Glocker, Ben},journal={Transactions on Machine Learning Research},year={2022},selected=true,}
@inproceedings{bannur2021hierarchical,title={Hierarchical analysis of visual COVID-19 features from chest radiographs},author={Bannur, Shruthi and Oktay, Ozan and Bernhardt, Melanie and Schwaighofer, Anton and Jena, Rajesh and others},howpublished={ArXiv:2107.06618},booktitle={Presented at ICML 2021 Workshop on Interpretable Machine Learning in Healthcare.},year={2021},eprint={https://arxiv.org/abs/2107.06618},}
@article{bernhardt2020training,title={Training variational networks with multidomain simulations: Speed-of-sound image reconstruction},author={Bernhardt, Melanie and Vishnevskiy, Valery and Rau, Richard and Goksel, Orcun},journal={IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control},volume={67},number={12},pages={2584--2594},year={2020},publisher={IEEE},}