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. 2019 Nov 26;9:1313. doi: 10.3389/fonc.2019.01313

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Copyright © 2019 Bagher-Ebadian, Janic, Liu, Pantelic, Hearshen, Elshaikh, Movsas, Chetty and Wen.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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(A) Shows true positive plus true negative (TP+TN) of the optimal ANN (8:5:1) at different training epochs. (B) Shows true positive, true negative, false positive, and false negative of the optimal ANN at different training epochs. (C) Demonstrates the area under receiver operating characteristic (AUROC, Az test) value for different ANN structures. As shown in this figure, the ANN with five neurons in its only hidden layer shows the highest performance and is chosen as the optimal ANN. (D) Shows the average ROC of the optimal ANN along with optimal-cut-point of the ANN.