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Eike Petersen
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Slicing Through Bias: Explaining Performance Gaps in Medical Image Analysis Using Slice Discovery Methods
Vincent Olesen, Nina Weng, Aasa Feragen, Eike Petersen
Fast diffusion-based counterfactuals for shortcut removal and generation
Nina Weng, Paraskevas Pegios, Eike Petersen, Aasa Feragen, Siavash Bigdeli
Bias in context: What to do when complete bias removal is not an option
Sune H. Holm, Eike Petersen, Melanie Ganz-Benjaminsen, Aasa Feragen
Are Sex-Based Physiological Differences the Cause of Gender Bias for Chest X-Ray Diagnosis?
Nina Weng, Siavash Bigdeli, Eike Petersen, Aasa Feragen
Leveraging Shape and Spatial Information for Spontaneous Preterm Birth Prediction
Paraskevas Pegios, Emilie P. F. Sejer, Manxi Lin, Zahra Bashir, Morten B. S. Svendsen, Mads Nielsen, Eike Petersen, Anders N. Christensen, Martin Tolsgaard, Aasa Feragen
On (assessing) the fairness of risk score models
Eike Petersen, Melanie Ganz-Benjaminsen, Sune H. Holm, Aasa Feragen
Feature Robustness and Sex Differences in Medical Imaging: A Case Study in MRI-Based Alzheimer’s Disease Detection
Eike Petersen, Aasa Feragen, Maria L. da C. Zemsch, Anders Henriksen, Oskar E. W. Christensen, Melanie Ganz-Benjaminsen
The path toward equal performance in medical machine learning
Eike Petersen, Sune H. Holm, Melanie Ganz-Benjaminsen, Aasa Feragen