False Negatives
A false negative occurs when a test or assessment incorrectly indicates that a condition or characteristic is absent when it is actually present. For example, if a medical test fails to detect a disease in a patient who has it, the test result is a false negative. This can happen in various contexts, such as health screenings, security checks, or even software fault detection. False negatives can be concerning because they may lead to missed opportunities for intervention, continued risks, and the potential spread of unrecognized issues.
Additional Insights
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A false negative occurs when a test or assessment fails to identify a condition or outcome that is actually present. For example, if a medical test indicates a person does not have a disease when they actually do, that’s a false negative. In general knowledge contexts, it means missing or overlooking important information or events. This can lead to misunderstandings or incorrect conclusions, as it suggests everything is normal when there are underlying issues. Essentially, it’s a missed detection that can have significant consequences, often resulting in a false sense of security.