Standard noise-robust methods do not guarantee low clinical risk from false negatives in noisy medical labels, but combining them with cost-sensitive optimization reduces risk without harming utility.
(2024).Machine Learning with Noisy Labels: Definitions, Theory, Tech- niques and Solutions
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Risk-Aware Robust Learning: Reducing Clinical Risk under Label Noise in Medical Image Classification
Standard noise-robust methods do not guarantee low clinical risk from false negatives in noisy medical labels, but combining them with cost-sensitive optimization reduces risk without harming utility.