Post-discharge step count data enhances dynamic readmission risk prediction, and optimizing temporal windows and model types further improves discrimination and calibration.
Does optimizing temporal windows and model type improve discrimination and calibration for wearable-augmented post-discharge readmission risk prediction?
Optimizing temporal windows and model types for wearable step count data improves the accuracy of post-discharge readmission risk prediction.
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Post-discharge step count data enhance dynamic readmission risk prediction. Optimizing temporal windows and model type improves discrimination and calibration.
Bressman et al. (Wed,) reported a other. Post-discharge step count data enhances dynamic readmission risk prediction, and optimizing temporal windows and model types further improves discrimination and calibration.