An ensemble model for predicting dispositions of emergency department patients
Kuang-Ming Kuo,
Yih-Lon Lin,
Chao Sheng Chang
et al.
Abstract:Objective
The healthcare challenge driven by an aging population and rising demand is one of the most pressing issues leading to emergency department (ED) overcrowding. An emerging solution lies in machine learning’s potential to predict ED dispositions, thus leading to promising substantial benefits. This study’s objective is to create a predictive model for ED patient dispositions by employing ensemble learning. It harnesses diverse data types, including structured and unstructured informatio… Show more
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