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arXiv Machine Learning By Benjamin T. Pike

Physiological Trajectories and Observation Patterns in ICU Mortality Prediction: Transportability Under Changing Measurement Conditions

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The study examined how physiological trajectories and observation patterns influence ICU mortality prediction across different datasets (MIMIC‑III, MIMIC‑IV, eICU). Models incorporating longitudinal physiological summaries (R2) consistently improved external prediction, while observation‑pattern features (R3) mainly benefited locally developed models and were highly sensitive to measurement timing and availability. The findings highlight that the transportability of clinical prediction models depends not only on patient populations but also on the conditions under which measurements are collected.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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