Sensitivity and specificity

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Sensitivity and specificity

Sensitivity (pronounced: sen-si-tiv-i-tee) and specificity (pronounced: spe-si-fis-i-tee) are statistical measures of the performance of a binary classification test, also known in statistics as a classification function.

Etymology

The term 'sensitivity' originates from the Latin word 'sensitivus', meaning 'capable of sensation', while 'specificity' comes from the Latin word 'specificus', meaning 'constituting a species or kind'.

Sensitivity

In medical diagnosis, sensitivity is the ability of a test to correctly identify those with the disease (true positive rate), whereas specificity is the ability of the test to correctly identify those without the disease (true negative rate).

Specificity

Specificity measures the proportion of negatives that are correctly identified as such (e.g., the percentage of healthy people who are correctly identified as not having the condition).

Related Terms

  • Positive predictive value: This is the probability that subjects with a positive screening test truly have the disease.
  • Negative predictive value: This is the probability that subjects with a negative screening test truly don't have the disease.
  • Prevalence: This is the total number of cases of a disease in the population at a given time.
  • Accuracy: This is the closeness of the measurements to a specific value.
  • Receiver operating characteristic: This is a graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied.

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