Interpreting ROC curves involves analyzing both the shape of the curve and the AUC value. A curve closer to the top-left corner indicates better performance. Here are some key interpretations: - AUC = 1: Perfect test. - **0.9 ≤ AUC Advantages of Using ROC Curves ROC curves offer several advantages: 1. Threshold Independence: They provide a way to evaluate the test's performance across all possible thresholds. 2. Comparison Tool: ROC curves allow for direct comparison of multiple diagnostic tests or models. 3. Visual Representation: They offer a visual method to understand the trade-offs between sensitivity and specificity.
