Fig. 4 | Scientific Reports

Fig. 4

From: Assessment of PTSD in military personnel via machine learning based on physiological habituation in a virtual immersive environment

Fig. 4

(a) Left: ROC curve of the prediction model. (b) Right: Confusion matrix (with normalized values in parentheses) of the model’s binary prediction for the test participants. With a binary accuracy of 80.95%, the model had a true negative rate (TNR) of 100% but a true positive rate (TPR) of 60%, meaning that 4 out of 10 participants with PTSD were not well detected. However, the ROC curve on the left indicates that this value could be increased to 80% at the cost of a slightly deteriorated false positive rate, meaning that more participants without PTSD would be predicted to have a PTSD. Depending on how important not missing any potential participants with PTSD is considered in the model, possibly optimal models could be fine-tuned with the desired TPR/TNR thresholds.

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