In medicine and statistics, sensitivity and specificity mathematically describe the accuracy of a test that reports the presence or absence of a medical condition.

In short, sensitivity and specificity describe the test’s intrinsic ability to detect or rule out a condition across populations with and without the condition in a controlled setting.

When a diagnostic test has high sensitivity and specificity, that means the test has a high likelihood of accurately identifying those with disease and those without disease (or illness).

Sensitivity: the ability of a test to correctly identify patients with a disease. Specificity: the ability of a test to correctly identify people without the disease. True positive: the person has the disease and the …

Sensitivity is a measure of how well a given test identifies the disease or trait in question (i.e., how well it avoids false negatives), while specificity is a measure of how well a given test identifies the absence …

Sensitivity and specificity are measures of a diagnostic test's accuracy. Sensitivity refers to the test's ability to correctly identify individuals with a disease, while specificity refers to its ability to correctly …

Sep 4, 2025 · In summary, sensitivity and specificity are fundamental metrics for evaluating the performance of diagnostic tests. Sensitivity gauges how well a test detects disease when it is …

Jul 23, 2025 · Sensitivity ensures that the true positives aren't missed whereas specificity ensures that false positives are labelled correctly. A model which has a high sensitivity but low specificity would …

Mar 14, 2026 · Sensitivity measures how well a test detects people who have a condition. Specificity measures how well it identifies people who don’t.

Aug 3, 2023 · In medical tests, sensitivity is the extent to which actual positives are not overlooked (so false negatives are few), and specificity is the extent to which actual negatives are classified as such …