6 papers
Proper Scoring Rules for Right-Censored Survival Data
Jef Jonkers, Glenn Van Wallendael, Luc Duchateau +1
Proper scoring rules provide a rigorous theoretical basis for the training and evaluation of probabilistic forecasts. However, in the presence of right censoring, the event time is…
Conformal Prediction for Dose-Response Models with Continuous Treatments
Jarne Verhaeghe, Jef Jonkers, Sofie Van Hoecke
Understanding the dose-response relation between a continuous treatment and the outcome for an individual can greatly drive decision-making, particularly in areas like personalized…
From Haystack to Needle: Label Space Reduction for Zero-shot Classification
Nathan Vandemoortele, Bram Steenwinckel, Femke Ongenae +1
We present Label Space Reduction (LSR), a novel method for improving zero-shot classification performance of Large Language Models (LLMs). LSR iteratively refines the classificatio…
Conformal Convolution and Monte Carlo Meta-learners for Predictive Inference of Individual Treatment Effects
Jef Jonkers, Jarne Verhaeghe, Glenn Van Wallendael +2
Generating probabilistic forecasts of potential outcomes and individual treatment effects (ITE) is essential for risk-aware decision-making in domains such as healthcare, policy, m…
landmarker: a Toolkit for Anatomical Landmark Localization in 2D/3D Images
Jef Jonkers, Luc Duchateau, Glenn Van Wallendael +1
Anatomical landmark localization in 2D/3D images is a critical task in medical imaging. Although many general-purpose tools exist for landmark localization in classical computer vi…
Reliable uncertainty quantification for 2D/3D anatomical landmark localization using multi-output conformal prediction
Jef Jonkers, Frank Coopman, Luc Duchateau +2
Automatic anatomical landmark localization in medical imaging requires not just accurate predictions but reliable uncertainty quantification for effective clinical decision support…