Machine Learning Approaches to Predict Hospital Readmissions: A Systematic Review
Abstract
This systematic review synthesizes current research on machine learning methods aimed at predicting hospital readmissions. We analyzed various studies that employed different algorithms, including logistic regression, decision trees, and neural networks. Our findings indicate that ML techniques significantly improve the accuracy of readmission predictions compared to traditional methods. This paper emphasizes the importance of implementing AI solutions to reduce readmission rates and enhance overall healthcare efficiency.
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