Why the study?
Hospital readmissions are a major challenge affecting patient outcomes and costs, and predictive modeling may enable early identification and intervention for preventable readmissions.
Does a Random Forest machine learning model improve prediction of 30-day hospital readmissions compared to Logistic Regression and LightGBM in adult admissions?
Does a Random Forest machine learning model improve prediction of 30-day hospital readmissions compared to Logistic Regression and LightGBM in adult admissions?
Machine learning models, particularly Random Forest, can improve 30-day readmission risk prediction to inform targeted healthcare interventions.
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May aid readmission risk stratification in community hospitals; leaves open prospective validation before clinical use.
Halac et al. (2024) studied this question.
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