Predicting Hospital Length of Stay Using Light Gradient Boosting Machine Regression

Length of stay (LoS) in a hospital is an important metric in the healthcare management system, with profound implications for resource allocation, patient outcomes, and cost reduction. This paper reviews the literature on approaches for predicting hospital length of stay with a R2 score of 96.14 per cent using Light Gradient Boosting Machine regressor. We critically assess the merits and limitations of various methods and propose a unified framework for the generalized prediction of length of stay. Our framework includes investigating the types of routinely collected data and recommendations for robust knowledge modelling.