Signal Fidelity Index-aware calibration for addressing distributional shift in predictive modeling across heterogeneous real-world data.

Abstract excerpt

Machine learning models trained on real-world data (RWD) often experience performance degradation when deployed across different settings due to distributional shift. However, a fundamental but under-explored factor contributing to this degradation is the decay of diagnostic signals: systematic variability in diagnostic quality and consistency across institutional contexts, which affects the reliability of...

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