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  2. Precision and recall - Wikipedia

    en.wikipedia.org/wiki/Precision_and_recall

    In pattern recognition, information retrieval, object detection and classification (machine learning), precision and recall are performance metrics that apply to data retrieved from a collection, corpus or sample space. Precision (also called positive predictive value) is the fraction of relevant instances among the retrieved instances.

  3. Sensitivity and specificity - Wikipedia

    en.wikipedia.org/wiki/Sensitivity_and_specificity

    Medical usage. In medical diagnosis, test sensitivity is the ability of a test to correctly identify those with the disease (true positive rate), whereas test specificity is the ability of the test to correctly identify those without the disease (true negative rate). If 100 patients known to have a disease were tested, and 43 test positive ...

  4. Receiver operating characteristic - Wikipedia

    en.wikipedia.org/wiki/Receiver_operating...

    A receiver operating characteristic curve, or ROC curve, is a graphical plot that illustrates the performance of a binary classifier model (can be used for multi class classification as well) at varying threshold values. The ROC curve is the plot of the true positive rate (TPR) against the false positive rate (FPR) at each threshold setting.

  5. Positive and negative predictive values - Wikipedia

    en.wikipedia.org/wiki/Positive_and_negative...

    The positive predictive value (PPV), or precision, is defined as = + = where a "true positive" is the event that the test makes a positive prediction, and the subject has a positive result under the gold standard, and a "false positive" is the event that the test makes a positive prediction, and the subject has a negative result under the gold standard.

  6. Rivalta test - Wikipedia

    en.wikipedia.org/wiki/Rivalta_test

    The Rivalta Test is a simple, inexpensive method that can be used in resource-limited settings to differentiate a transudate from an exudate. [1] It is a simple, inexpensive method that does not require special laboratory equipment and can be easily performed in private practice. The test was originally developed by the Italian researcher ...

  7. Pre- and post-test probability - Wikipedia

    en.wikipedia.org/wiki/Pre-_and_post-test_probability

    Pre-test probability and post-test probability (alternatively spelled pretest and posttest probability) are the probabilities of the presence of a condition (such as a disease) before and after a diagnostic test, respectively. Post-test probability, in turn, can be positive or negative, depending on whether the test falls out as a positive test ...

  8. 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 ...

  9. Likelihood ratios in diagnostic testing - Wikipedia

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

    In evidence-based medicine, likelihood ratios are used for assessing the value of performing a diagnostic test. 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 ...