2 citations · 3 across the 6 of their papers we have counts for
3 papers · 1 filter
How Many Labels Are Enough? ALDA: Active Learning Deployment Advisor for Medical Image Classification
Julia Machnio, Mads Nielsen, Mostafa Mehdipour Ghazi
Active learning (AL) promises to reduce the cost of medical imaging projects by lowering the number of clinical labels required. However, practical deployment requires committing t…
A Mechanism-Driven Theory of Phase Transitions in Active Learning
Julia Machnio, Mads Nielsen, Mostafa Mehdipour Ghazi
Active learning (AL) performance is known to be budget-dependent, yet regimes are typically defined by heuristic label counts that fail to generalize across datasets or architectur…
Towards Brain MRI Foundation Models for the Clinic: Findings from the FOMO25 Challenge
Asbjørn Munk, Stefano Cerri, Vardan Nersesjan +81
Clinical deployment of automated brain MRI analysis faces a fundamental challenge: clinical data is heterogeneous and noisy, and high-quality labels are prohibitively costly to obt…