Diagnostics for Individual-Level Prediction Instability in Machine Learning for Healthcare

ArXi:2603.00192v2 Announce Type: replace In healthcare, predictive models increasingly inform patient-level decisions, yet little attention is paid to the variability in individual risk estimates and its impact on treatment decisions. For overparameterized models, now standard in machine learning, a substantial source of variability often goes undetected. Even when the data and model architecture are held fixed, randomness