Fig 3. Comparison of miRAW’s neural network performance with the positive and negative training datasets when using a negative log likelihood (NLL) loss function and a cross entropy loss function (XENT) with 10 fold cross validation.

XENT provides significantly better accuracy, precision, sensitivity, specificity, F1-scores and area under the curve (AUC) compared to NLL (* p-value < 0.05, ** p-value < 0.01).