Predicting Hospital Length of Stay Using Neural Networks on MIMIC III Data
Thanos Gentimis, Ala’ J. Alnaser, Alex Durante, Kyle Cook, Robert JC Steele · 2017
In this paper we explore the use of neural networksfor predicting the total length of stay for patients with various diagnoses based on selected general characteristics. A neural network is trained to predict whether patient stay will be long ( 5 days), or short (≤ 5 days) as of the time the patient leaves the ICU unit. Our dataset is drawn from the MIMIC III database and all code was written in R and in Postgress, while the computations were executed on the Florida Polytechnic University's supercomputer. Our prediction accuracy is approximately 80% and clearly outperforms any linear model.