Medical Diagnostic Test — Confusion Matrix & Metrics Calculator
Compute accuracy, precision, recall, F1, specificity, MCC and more for medical diagnostic test from TP/FP/FN/TN counts.
Medical screening lives and dies by sensitivity (recall) and specificity, plus the often-misunderstood positive predictive value — which depends heavily on disease prevalence. This tool computes all of them and is built to teach why a 99%-accurate test can still be wrong most of the time it says 'positive'.
Formula
Note: Educational tool for understanding diagnostic-test statistics. Not medical advice; clinical test interpretation must be done by qualified professionals accounting for real prevalence and individual factors.
Disclaimer: This tool is for general informational and estimation purposes only and is not professional financial, tax, accounting or legal advice. All figures are estimates — verify with a qualified professional before making decisions. Read the full disclaimer.
About Medical Diagnostic Test — Confusion Matrix & Metrics Calculator
Medical screening lives and dies by sensitivity (recall) and specificity, plus the often-misunderstood positive predictive value — which depends heavily on disease prevalence. This tool computes all of them and is built to teach why a 99%-accurate test can still be wrong most of the time it says 'positive'. Enter the four confusion-matrix counts and this calculator returns every standard metric — accuracy, precision, recall (sensitivity), F1, specificity and the Matthews correlation coefficient — recomputed live. MCC is highlighted because it is the most honest single number for imbalanced problems: it only scores high when the model does well across all four quadrants, unlike accuracy or F1 which can be gamed.
How to use Medical Diagnostic Test — Confusion Matrix & Metrics Calculator
- 1Enter your values into Medical Diagnostic Test — Confusion Matrix & Metrics Calculator — sensible, domain-typical defaults are pre-filled so you see a real result immediately.
- 2The result recomputes live using the formula shown on the page; there is no button to press.
- 3Adjust any input to compare scenarios, then read the worked example to see the substituted numbers.
Why use Medical Diagnostic Test — Confusion Matrix & Metrics Calculator?
- ✓Computes Medical Diagnostic Test instantly in your browser — no sign-up, no upload, no server round-trip.
- ✓100% free and unlimited, with the exact formula shown: precision = TP/(TP+FP).
- ✓Runs entirely client-side, so every value you enter stays private on your device.
- ✓Live recompute as you type, with a worked example and authoritative references for trust.
Frequently asked questions
Sensitivity vs specificity — which matters for a screening test?+
Screening tests prioritize sensitivity (recall): catch every true case even at the cost of false alarms, because missing a disease is worse than a follow-up test. Confirmatory tests then prioritize specificity to weed out the false positives the screen generated.
Why can a positive result from an accurate test still likely be wrong?+
Base rates. For a rare disease (say 0.5% prevalence), even a 95%-specific test produces far more false positives (from the huge healthy majority) than true positives — so positive predictive value is low. This is the base-rate fallacy, and PPV makes it explicit.
Why is MCC considered the most reliable single metric?+
MCC uses all four confusion-matrix cells and behaves like a correlation coefficient (−1 to +1): it is high only when predictions track reality across both classes. On imbalanced data where accuracy and even F1 can mislead, MCC stays informative — which is why it's increasingly the recommended summary statistic.
What's the difference between recall and specificity?+
Recall (sensitivity) is the fraction of actual disease present cases the model catches — TP/(TP+FN). Specificity is the fraction of actual healthy cases it correctly clears — TN/(TN+FP). A model can have high recall and low specificity (flags everything) or vice versa; you need both to judge it.
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