A weighted mean of overall sensitivity and specificity was derived and used to create an ROC curve. Alternative metrics Comprehensiveness and Relevance were calculated for each case and compared to the other measures. Weighted mean sensitivity closely matched Comprehensiveness and mean PPV matched Relevance. Plotting the Physician's sensitivity and specificity on the ROC curve showed that their discrimination was similar to the HDP but sensitivity was significantly lower. These metrics give a clear picture of a program's diagnostic performance and allow straightforward comparison between different programs and different studies.
Heart failure is a complex multisystem disease in which several predictors are categorical.
Neural network models have successfully been applied to several medical classification problems. Given the small number of cases, the neural network model was trained using a resampling method. Only 9 individuals were missclassified. Neural networks have the potential to be a useful tool for making prognosis in the domain of heart failure. Dx Decision support Comp.