Randomness from model optimization and initialization causes individual risk predictions in flexible ML models to vary as much as resampling the full training data, potentially flipping clinical decisions near thresholds.
All models are wrong and yours are useless: making clinical prediction models impactful for patients.npj Precision Oncology, 8(1):54, 2024
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Diagnostics for Individual-Level Prediction Instability in Machine Learning for Healthcare
Randomness from model optimization and initialization causes individual risk predictions in flexible ML models to vary as much as resampling the full training data, potentially flipping clinical decisions near thresholds.