title: A comparison of ICU mortality prediction using the APACHE II scoring system and artificial neural networks.
abstract: The aim of this study was to compare the ability of artificial neural networks and the Acute Physiology and Chronic Health Evaluation II score to predict mortality in adult intensive care units. The same physiological variables were used in both predictive models to predict hospital mortality from a data set of 8796 patients collected from 26 adult intensive care units in the United Kingdom and Ireland as part of the Intensive Care Society study. The results from the two models were compared with the actual outcome. The overall prediction accuracy and the overall goodness-of-fit of all the models were assessed. Both predictive models showed similar goodness-of-fit and prediction discrimination. The overall predictive and classification performance of the artificial neural network developed matched and in some aspects was better than that of Acute Physiology and Chronic Health Evaluation II.
authors.affiliation: Nuffield Department of Anaesthetics, Radcliffe Infirmary, Oxford, UK.
authors.forename: L S
authors.initials: LS
authors.lastname: Wong
authors.forename: J D
authors.initials: JD
authors.lastname: Young
mesh_terms: D018806:APACHE; D000328:Adult; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D007494:Ireland / Q000453:epidemiology; D016571:Neural Networks, Computer; D015203:Reproducibility of Results; D006113:United Kingdom / Q000453:epidemiology