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  2. False positive rate - Wikipedia

    en.wikipedia.org/wiki/False_positive_rate

    The false positive rate is calculated as the ratio between the number of negative events wrongly categorized as positive (false positives) and the total number of actual negative events (regardless of classification). The false positive rate (or "false alarm rate") usually refers to the expectancy of the false positive ratio.

  3. False positives and false negatives - Wikipedia

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

    The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present. The false positive rate is equal to the significance level. The specificity of the test is equal to 1 minus the false positive rate.

  4. 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.

  5. Clearblue - Wikipedia

    en.wikipedia.org/wiki/Clearblue

    Clearblue was introduced in 1985 with the launch of the first Clearblue Home Pregnancy Test system, which at the time was owned by Unilever. [4] It was the world’s first “rapid home test” that gave pregnancy test results in 30 minutes and allowed a woman to take a test before going to the doctor. [ 4 ]

  6. Are False Positive Covid Tests Common? Doctors Explain. - AOL

    www.aol.com/false-positive-covid-tests-common...

    A false positive Covid-19 test result can happen, but it’s rare, says Brian Labus, Ph.D., M.P.H., assistant professor at the University of Nevada Las Vegas School of Public Health.

  7. Sensitivity and specificity - Wikipedia

    en.wikipedia.org/wiki/Sensitivity_and_specificity

    The true positive in this figure is 6, and false negatives of 0 (because all positive condition is correctly predicted as positive). Therefore, the sensitivity is 100% (from 6 / (6 + 0) ). This situation is also illustrated in the previous figure where the dotted line is at position A (the left-hand side is predicted as negative by the model ...

  8. How common are false-positive COVID tests? Experts weigh in.

    www.aol.com/lifestyle/common-false-positive...

    The false-positive rate for a PCR test is close to zero, though. ... Both BinaxNOW and QuickVue recommend that you take two tests at least 24 to 36 hours apart to get the most accurate results.

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