3 papers
eess.IV2026
Medical Image Analysis with Machine Learning (MEDiml): Strategies for Simpler Radiomics
Mahdi Ait Lhaj Loutfi, Simon Provost, Élodie Gillard +13
Radiomics extracts quantitative features describing tumor shape, intensity, and texture from medical images to build models that predict clinical outcomes. However, large feature s…
cs.LG2026
Diagnosing Low-Confidence Patient Profiles via Localized Harmful Covariate Shift Detection
Olivier Lefebvre, Hakima Laribi, Dan Poenaru +1
Before deploying clinical prediction models, their reliability must be assessed to ensure safe use. Errors may arise from distribution shifts between training and deployment or fro…
q-bio.QM2022
Machine learning strategies to predict late adverse effects in childhood acute lymphoblastic leukemia survivors
Nicolas Raymond, Maxime Caru, Hakima Laribi +6
Acute lymphoblastic leukemia is the most frequent pediatric cancer. Approximately two third of survivors develop one or more health complications known as late adverse effects foll…