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Hospital Readmission Prediction by anji0797 is a document available to read on EtoBox.

This study developed and evaluated machine learning models to predict 30-day hospital readmissions using both manually-derived and automatically-generated features from longitudinal data. The analysis included 428,669 patients, revealing that the machine learning model significantly outperformed the conventional LACE model, achieving an AUC of 0.83 compared to LACE

Author
anji0797
Language
EN