3 papers
cs.LG2026
Intersectional Disentangling of Temporal and Acquisition Bias in Fetal Ultrasound
Aya Elgebaly, Joris Fournel, Benjamin Laine Jønch Jurgensen +6
Fairness studies of medical imaging AI often explain subgroup performance gaps through under-representation in the training data. We show that intersectional analysis can disentang…
cs.CV2024
Guided Synthesis of Labeled Brain MRI Data Using Latent Diffusion Models for Segmentation of Enlarged Ventricles
Tim Ruschke, Jonathan Frederik Carlsen, Adam Espe Hansen +4
Deep learning models in medical contexts face challenges like data scarcity, inhomogeneity, and privacy concerns. This study focuses on improving ventricular segmentation in brain…
cs.CL2024
Classification of Radiological Text in Small and Imbalanced Datasets in a Non-English Language
Vincent Beliveau, Helene Kaas, Martin Prener +5
Natural language processing (NLP) in the medical domain can underperform in real-world applications involving small datasets in a non-English language with few labeled samples and…