false positive/negative
[FAWLS PAH-zuh-tiv / NEG-uh-tiv]
nounpl: false positives/negatives
falso positivo/falso negativo
1. A false positive is an incorrect test result indicating the presence of a condition when it is actually absent; a false negative is an incorrect test result indicating the absence of a condition when it is actually present
The COVID-19 test came back positive, but it was a false positive—the patient did not actually have the virus.
O teste de COVID-19 deu positivo, mas foi um falso positivo—o paciente não tinha o vírus.
2. In statistics and machine learning, erroneous outcomes where predicted classifications do not match actual results
The algorithm had too many false positives, flagging legitimate emails as spam.
O algoritmo tinha muitos falsos positivos, marcando e-mails legítimos como spam.
3. In quality control and testing, results that incorrectly indicate success or failure
A false negative in a cancer screening can delay critical treatment.
Um falso negativo em uma triagem de câncer pode atrasar o tratamento crítico.
These terms are essential in both Brazilian and American healthcare, technology, and scientific contexts. In Brazil, with increasing COVID-19 testing and digital service adoption, understanding false positives/negatives became culturally significant during the pandemic. In the USA, these terms are fundamental to discussions about medical testing accuracy, especially in contexts like cancer screening, drug testing, and cybersecurity. The terminology is standardized across both countries in medical and academic literature.
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