Sensitivity
Sensitivity refers to the ability of a test to correctly identify individuals with a disease or condition. In medical terms, it is the proportion of true positive results in the population. It is a measure of how well a test can identify true positives.
Definition[edit | edit source]
Sensitivity is defined as the proportion of true positive results in the population. It is calculated as the number of true positives divided by the sum of true positives and false negatives. This means that a test with high sensitivity will correctly identify a high proportion of individuals who have the disease, but may also incorrectly identify some individuals who do not have the disease (false positives).
Calculation[edit | edit source]
The formula for calculating sensitivity is:
Sensitivity = (True Positives) / (True Positives + False Negatives)
This formula gives the proportion of true positive results in the population. A test with high sensitivity will have a high proportion of true positives and a low proportion of false negatives.
Importance[edit | edit source]
Sensitivity is an important measure of the performance of a diagnostic test. A test with high sensitivity is able to correctly identify a high proportion of individuals who have the disease, which is important in preventing the spread of the disease and in ensuring that individuals receive appropriate treatment. However, a test with high sensitivity may also have a high rate of false positives, which can lead to unnecessary treatment and anxiety.
See also[edit | edit source]
References[edit | edit source]
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Contributors: Prab R. Tumpati, MD