%0 Generic %A Tang, Zi-Hui %A Liu, Juanmei %A Zeng, Fangfang %A Li, Zhongtao %A Yu, Xiaoling %A Zhou, Linuo %D 2013 %T Comparisons between models from Multiple logistic regression and Artificial neural network analysis. %U https://plos.figshare.com/articles/dataset/_Comparisons_between_models_from_Multiple_logistic_regression_and_Artificial_neural_network_analysis_/764775 %R 10.1371/journal.pone.0070571.t005 %2 https://ndownloader.figshare.com/files/1143290 %K Computer applications %K Applied mathematics %K Probability theory %K statistics %K Biostatistics %K Statistical methods %K cardiovascular %K Endocrinology %K neurology %K Non-clinical medicine %K Evidence-based medicine %K logistic %K regression %K neural %X

Note: Comparison analysis to parameters of LR and ANN models used noninferiority tests; the null hypothesis was parameters of ANN model were inferior to parameters of LR model (as reference). AUC-Area under the receiver-operating curve, PPV = positive predictive value; NPV = negative predictive value.

%I PLOS ONE