Biomarker Diagnostic Threshold — 2D ROC Curve Explorer

Every blood-test cutoff — troponin, PSA, HbA1c, a tumour marker — is a line drawn through two overlapping bell curves: one for healthy patients, one for diseased ones. This simulator draws both populations as true Gaussian density curves with a jittered strip of the real sampled patients underneath, lets you drag the diagnostic threshold through the overlap, and recomputes the confusion matrix, sensitivity, specificity and PPV directly from the sampled points on every move. A live ROC panel traces the analytic curve from the underlying Gaussian parameters and marks exactly where the current cutoff sits on it, so you can see how widening the gap between population means or tightening their spread turns a mediocre test into a decisive one — and why no single cutoff can maximise both sensitivity and specificity at once.