False negative is identifying someone as non-dangerous when they in fact go on to commit a dangerous act. When trying to identify dangerous offenders, researchers often make mistakes. One of these mistakes is known as a False Positive. The false negative error is identifying someone as dangerous when they are not dangerous. False negative pregnancy tests don't really happen, as long as you're taking the test correctly. Another common reason for getting a false negative is not having enough hCG in your urine. This may happen if you drank a lot of water, diluting your urine. False negative is a result that appears negative when it should not. An example of a false negative would be if a particular test designed to detect cancer returns a negative result but the person actually does have cancer.
As more people are tested for COVID-19, experts are warning the results might not be 100 percent accurate. “The major concern for false negatives is someone who tests negative, thinking they are not infected, could unknowingly spread the virus into the community.” - Dr. Gary L. LeRoy, FAAFP, president of the American Academy of Family Physicians, told Healthline.
“You can have a false negative if you have very little virus up there or perhaps the specimen was taken inappropriately. It didn’t get up high enough to actually get to the place where the virus was located. That’s another possibility,” - Dr. William Schaffner, an infectious disease specialist at Vanderbilt University Medical Center in Tennessee, told Healthline.
False-negative results could enable transmission of any infection to the family and the society. Take CT count on a Covid Report. A COVID report always mentions a CT count, which gives the suspected patient an idea as to how many cycles were needed to detect the DNA of the SARS-COV-2 virus.
The concept of Bayes' theorem is that true rates of false positives and false negatives are not a function of the accuracy of the test alone, but also the actual rate or frequency of occurrence within the test population.
Type II errors or false negative errors are the error of accepting something that should have been rejected; e.g., such as finding a guilty person innocent. A false negative error is a test result that indicates that a condition does not hold, while in fact it does. In other words, erroneously, no effect has been inferred.
An example for a false negative is a test indicating that a woman is not pregnant whereas she is actually pregnant. Another example is a truly guilty prisoner who is acquitted of a crime. A false negative error is a type error or type II error, occurring in a test where a single condition is checked for and the result of the test is erroneously that the condition is absent.
A false negative occurs when a spam email is not detected as spam, but is classified as "non-spam".
A low number of false negatives is an indicator of the efficiency of "spam filtering" methods.