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Distribution shift detection for the postmarket surveillance of medical AI algorithms: a retrospective simulation study
22
Zitationen
3
Autoren
2024
Jahr
Abstract
). All methods identified easier-to-detect out-of-distribution shifts with small (≤300) sample sizes. We conclude that effective tools exist for detecting clinically relevant distribution shifts. In particular classifier-based tests can be easily implemented components in the post-market surveillance strategy of medical device manufacturers.
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