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  2. Pregnancy test - Wikipedia

    en.wikipedia.org/wiki/Pregnancy_test

    A systematic review published in 1998 showed that home pregnancy test kits, when used by experienced technicians, are almost as accurate as professional laboratory testing (97.4%). When used by consumers, however, the accuracy fell to 75%: the review authors noted that many users misunderstood or failed to follow the instructions included in ...

  3. Pregnancy tests using animals - Wikipedia

    en.wikipedia.org/wiki/Pregnancy_tests_using_animals

    Before immunological pregnancy tests were developed in the 1960s, women relied on urine-based pregnancy tests using animals, ranging from mice to frogs. [1] [2] Advancements in medical technology have enabled women to accurately check their pregnancy status by using 'pee-on-a-stick' pregnancy test kits at home. Before these accessible and ...

  4. *This* Is The Best Time Of Day To Take A Pregnancy Test For ...

    www.aol.com/best-time-day-pregnancy-test...

    How accurate are home pregnancy tests? Every test is slightly different and the time you take it matters, too, Dr. Greves says. Many tests claim to be 99% accurate, but research from the ...

  5. Rabbit test - Wikipedia

    en.wikipedia.org/wiki/Rabbit_test

    The rabbit test became a widely used bioassay (animal-based test) to test for pregnancy. The term "rabbit test" was first recorded in 1949, and was the origin of a common euphemism, "the rabbit died", for a positive pregnancy test. [4] The phrase was, in fact, based on a common misconception about the test.

  6. Fertility awareness - Wikipedia

    en.wikipedia.org/wiki/Fertility_awareness

    Pregnancy tests are not accurate until 1–2 weeks after ovulation. Knowing an estimated date of ovulation can prevent a woman from getting false negative results due to testing too early. Also, 18 consecutive days of elevated temperatures means a woman is almost certainly pregnant. [61]

  7. 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.

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