Model comparison in Emergency Severity Index level prediction
We model ESI prediction using data from 870 patients over one month in 2008. Three methods are compared: regression, Bayesian networks and neural networks. Saturated oxygen level and chief complaint are significant predictors of ESI level. Models performed best using all data and had about 68% accuracy. Nave Bayesian networks are recommended over neural networks and logistic regression.
neural networks nave bayesian networks ordinal logistic regression emergency severity index (esi)