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Binary Test Errors
[By staff reporters]
In medical testing, and more generally in binary classification, a false positive is an error in data reporting in which a test result improperly indicates presence of a condition, such as a disease (the result is positive), when in reality it is not present, while a false negative is an error in which a test result improperly indicates no presence of a condition (the result is negative), when in reality it is present.
Assessment
These are the two kinds of errors in a binary test (and are contrasted with a correct result, either a true positive or a true negative.) They are also known in medicine as a false positive (respectively negative) diagnosis, and in statistical classification as a false positive (respectively negative) error.
A false positive is distinct from overdiagnosis, and is also different from overtesting.
Conclusion: Your thoughts are appreciated.
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