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  2. Sensitivity and specificity - Wikipedia

    en.wikipedia.org/wiki/Sensitivity_and_specificity

    Sensitivity and specificity values alone may be highly misleading. The 'worst-case' sensitivity or specificity must be calculated in order to avoid reliance on experiments with few results. For example, a particular test may easily show 100% sensitivity if tested against the gold standard four times, but a single additional test against the ...

  3. False positives and false negatives - Wikipedia

    en.wikipedia.org/wiki/False_positives_and_false...

    The specificity of the test is equal to 1 minus the false positive rate. In statistical hypothesis testing, this fraction is given the Greek letter α, and 1 − α is defined as the specificity of the test. Increasing the specificity of the test lowers the probability of type I errors, but may raise the probability of type II errors (false ...

  4. Sensitivity - Wikipedia

    en.wikipedia.org/wiki/Sensitivity

    Sensitivity (physiology), the ability of an organism or organ to respond to external stimuli Sensory processing sensitivity, a personality trait in humans; Sensitivity and specificity, statistical measures of the performance of binary classification tests; Allergic sensitivity, the strength of a reaction to an allergen

  5. Gold standard (test) - Wikipedia

    en.wikipedia.org/wiki/Gold_standard_(test)

    A hypothetical ideal "gold standard" test has a sensitivity of 100% concerning the presence of the disease (it identifies all individuals with a well-defined disease process; it does not have any false-negative results) and a specificity of 100% (it does not falsely identify someone with a condition that does not have the condition; it does not have any false-positive results).

  6. Precision and recall - Wikipedia

    en.wikipedia.org/wiki/Precision_and_recall

    In a classification task, the precision for a class is the number of true positives (i.e. the number of items correctly labelled as belonging to the positive class) divided by the total number of elements labelled as belonging to the positive class (i.e. the sum of true positives and false positives, which are items incorrectly labelled as belonging to the class).

  7. Likelihood ratios in diagnostic testing - Wikipedia

    en.wikipedia.org/wiki/Likelihood_ratios_in...

    They use the sensitivity and specificity of the test to determine whether a test result usefully changes the probability that a condition (such as a disease state) exists. The first description of the use of likelihood ratios for decision rules was made at a symposium on information theory in 1954. [ 1 ]

  8. Evaluation of binary classifiers - Wikipedia

    en.wikipedia.org/wiki/Evaluation_of_binary...

    The relationship between sensitivity and specificity, as well as the performance of the classifier, can be visualized and studied using the Receiver Operating Characteristic (ROC) curve. In theory, sensitivity and specificity are independent in the sense that it is possible to achieve 100% in both (such as in the red/blue ball example given above).

  9. COVID-19 testing - Wikipedia

    en.wikipedia.org/wiki/COVID-19_testing

    For ID NOW, the average sensitivity was 73.0% with an average specificity of 99.7%; for Xpert Xpress the average sensitivity was 100% with an average specificity of 97.2%. [33] [34] In a diagnostic test, sensitivity is a measure of how well a test can identify true positives and specificity is a measure of how well a test can identify true ...