Updating clinical AI models can cause prediction flips, arbitrariness, and unfair error rates across groups, requiring dedicated monitoring dimensions.
Mitigating catastrophic forgetting in medical imaging via incremental learning,
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An empirical evaluation of the risks of AI model updates using clinical data: stability, arbitrariness, and fairness
Updating clinical AI models can cause prediction flips, arbitrariness, and unfair error rates across groups, requiring dedicated monitoring dimensions.