In evidence-based medicine,<unk><unk>  are used for assessing the value of performing a<unk>  test. They use the sensitivity and specificity of the test to determine whether a test result usefully changes the probability that a condition (such as a disease state) exists. The first description of the use of<unk><unk>  for decision rules was made at a symposium on information theory in 1954. In medicine,<unk><unk>  were introduced between 1975 and 1980.
Likelihood ratios in diagnostic testing
Predictive value of tests
Inter-rater reliability
Sensitivity and specificity
Number needed to treat
Indicative limit value
Relative risk reduction
Real world data