Prediction of mortality in stroke patients using multilayer perceptron neural networks
نویسندگان
چکیده
Materials and methods: A data set consisting of 584 stroke patients was analyzed using MLP neural networks. Th e eff ect of prognostic factors (age, hospitalization time, sex, hypertension, atrial fi brillation, embolism, stroke type, infection, diabetes mellitus, and ischemic heart disease) on mortality in stroke were trained with 6 diff erent MLP algorithms [quick propagation (QP), Levenberg-Marquardt (LM), backpropagation (BP), quasi-Newton (QN), delta bar delta (DBD), and conjugate gradient descent (CGD)]. Th e performances of the MLP neural network algorithms were compared using the receiver operating characteristic (ROC) curve method.
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