| prediction rules |
Identifying and giving weight to the factors important in formulating a diagnosis, in order to establish the probability that a disease is present.
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| predictive v. |
the conditional probability that a clinical test result correctly identifies a patient as having or not having a disease, i.e., the predictive value of a positive test (positive predictive v.) is the probability that a person with a positive test is a true positive (i.e., does have the disease) and the predictive value of a negative test (negative predictive v.) is the probability that a person with a negative test does not have the disease. Cf. sensitivity and specificity. The predictive value of a screening test is determined by the sensitivity and specificity of the test, and by the prevalence of the condition for which the test is used.
출처: www.mercksource.com/pp/us/cns/cns_health_library.j...
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| predictive value |
In screening and diagnostic tests, the probability that a person with a positive test is a true positive (ie, does have the disease), or that a person with a negative test truly does not have the disease. The predictive value of a screening test is determined by the sensitivity and specificity of the test, and by the prevalence of the condition for which the test is used. Pre-test probability. Probability of disease, before performing a diagnostic test.
출처: www.cefpas.it/ebm/tools/glossary.htm
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| predictive value |
The statistic generated by dividing the number of true positives by the sum of the true positives and false positives (eg the number of cases with truly good care divided by the sum of the cases with truly good care plus those cases classified with good care who did not receive it - ie, the likelihood that a patient classified as the recipient of good care actually received good care).
출처: www.utmem.edu/CENTER/cgi/htmlos.cgi/004579.71.1265...
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