Flavio Ragni
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When uncertainty quantification fails: structural vulnerabilities and corrections for selective prediction under clinical class imbalance
According to the abstract, Endrizzi, Ragni, Marchesi and co-authors say uncertainty scores used by clinical AI to defer cases to human experts can become a proxy for class membership under severe class imbalance, penalizing minority patients. They test their corrections on synthetic conditions and three neurodegenerative cohorts.