Process / pipelinediagnostic-testing

Sensitivity and Specificity

Sensitivity and specificity are fundamental metrics of diagnostic test accuracy. Sensitivity is the probability that a test correctly identifies a person with the disease (true positive rate: TP / (TP + FN)). Specificity is the probability that a test correctly identifies a person without the disease (true negative rate: TN / (TN + FP)). Every test involves a trade-off: increasing sensitivity (catching all sick people) often reduces specificity (more false alarms). Choice of test threshold depends on the clinical context: screening for serious diseases favors sensitivity; confirming a diagnosis favors specificity.

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Sources

  1. Altman, D. G., & Bland, J. M. (1994). Diagnostic tests 1: Sensitivity and specificity. BMJ, 308(6943), 1552. DOI: 10.1136/bmj.308.6943.1552
  2. Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861–874. DOI: 10.1016/j.patrec.2005.10.010
  3. Metz, C. E. (1978). Basic principles of ROC analysis. Seminars in Nuclear Medicine, 8(4), 283–298. DOI: 10.1016/S0001-2998(78)80014-2

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Referenced by

ScholarGateSensitivity and Specificity (Sensitivity and Specificity in Diagnostic Testing and Binary Classification). Retrieved 2026-06-04 from https://scholargate.app/tr/research-statistics/sensitivity-specificity