Skip to main content
. Author manuscript; available in PMC: 2024 Sep 1.
Published in final edited form as: Lancet Digit Health. 2023 Jul 18;5(9):e551–e559. doi: 10.1016/S2589-7500(23)00094-8

Figure 2:

Figure 2:

Figure 2:

A. Predictive performance of the top five ML models after external validation according to receiver operating characteristic (ROC) curves. Areas under ROC curves (AUC) for ROC curves are shown with 95% confidence intervals (dotted curves). All five ML models presented with similar diagnostic performance in terms of AUC. The final selected ML model was a model (red) that did not utilize SDHB pathogenic variant status and presented with high MCC and balanced accuracy metrics. B. Comparison of the diagnostic performance of the selected ENS model with that of the twelve clinical care specialists according to their interpretations of likely presence or absence of metastatic disease. The classification performance of the ENS model, which was established without requirement of the SDHB pathogenic variant status, was significantly better than the performance of all specialists, both before (B1) and after provision of information about SDHB pathogenic variant status (B2).