Wolfgang Gaissmaier, Kevin E Tiede, Rocio Garcia-Retamero
The Lure of Beauty: People Select Representations of Statistical Information Largely Based on Attractiveness, Not Comprehensibility
Medical decision making : an international journal of the Society for Medical Decision Making
disease severity classification system widely used predict survival patients admitted intensive care unit different diagnoses present study conventional severity classification systems compared artificial intelligence predictive models artificial neural network decision tree terms prediction survival rate patients admitted intensive care unit retrospective cohort study performed data patients admitted icu ghaemshahrs razi teaching care center march 20th 2017 september 22nd 2019 required data calculating conventional severity classification models sofa saps ii apache ii apache iv collected patients medical records subsequently score model calculated artificial intelligence predictive models artificial neural network decision tree developed next step lastly performance model predicting survival patients admitted intensive care unit evaluated using criteria sensitivity specificity accuracy fmeasure area roc curve also model validated externally r program version 41 used create artificial intelligence models spss statistics software version 21 utilized perform statistical analysis area roc curve sofa saps ii apache ii apache iv multilayer perceptron artificial neural network cart decision tree 760 771 803 785 841 800 respectively results showed although apache ii model better results conventional models predicting survival rate patients admitted intensive care unit conventional models provided acceptable results moreover findings showed artificial neural network model best performance among studied models indicating discrimination power model predicting patient survival compared models