19 citations · 25 across the 7 of their papers we have counts for
4 papers · 1 filter
Performance Metrics for Probabilistic Ordinal Classifiers
Adrian Galdran
Ordinal classification models assign higher penalties to predictions further away from the true class. As a result, they are appropriate for relevant diagnostic tasks like disease…
Why is the winner the best?
Matthias Eisenmann, Annika Reinke, Vivienn Weru +122
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to in…
Multi-Head Multi-Loss Model Calibration
Adrian Galdran, Johan Verjans, Gustavo Carneiro +1
Delivering meaningful uncertainty estimates is essential for a successful deployment of machine learning models in the clinical practice. A central aspect of uncertainty quantifica…
Test Time Transform Prediction for Open Set Histopathological Image Recognition
Adrian Galdran, Katherine J. Hewitt, Narmin L. Ghaffari +3
Tissue typology annotation in Whole Slide histological images is a complex and tedious, yet necessary task for the development of computational pathology models. We propose to addr…