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MDCalc is a free online medical reference for healthcare professionals that provides point-of-care clinical decision-support tools, including medical calculators, scoring systems, and algorithms. [1] MDCalc is also a mobile and web app. [ 2 ] The decision-support tools are based on published clinical research, [ 3 ] and MDCalc’s content is ...
A medical calculator is a type of medical computer software, whose purpose is to allow easy calculation of various scores and indices, presenting the user with a friendly interface that hides the complexity of the formulas. Most offer further information such as result interpretation guides and medical literature references. [1]
However, "biostatistics" more commonly connotes all applications of statistics to biology. [2] Medical statistics is a subdiscipline of statistics. It is the science of summarizing, collecting, presenting and interpreting data in medical practice, and using them to estimate the magnitude of associations and test hypotheses.
In medicine and statistics, sensitivity and specificity mathematically describe the accuracy of a test that reports the presence or absence of a medical condition. If individuals who have the condition are considered "positive" and those who do not are considered "negative", then sensitivity is a measure of how well a test can identify true ...
The number needed to treat (NNT) or number needed to treat for an additional beneficial outcome (NNTB) is an epidemiological measure used in communicating the effectiveness of a health-care intervention, typically a treatment with medication. The NNT is the average number of patients who need to be treated to prevent one additional bad outcome.
The average treatment effect (ATE) is a measure used to compare treatments (or interventions) in randomized experiments, evaluation of policy interventions, and medical trials. The ATE measures the difference in mean (average) outcomes between units assigned to the treatment and units assigned to the control.
A medical example is the likelihood that a given test result would be expected in a patient with a certain disorder compared to the likelihood that same result would occur in a patient without the target disorder. Some sources distinguish between LR+ and LR−. [13] A worked example is shown below.
In medical testing with binary classification, the diagnostic odds ratio (DOR) is a measure of the effectiveness of a diagnostic test. [1] It is defined as the ratio of the odds of the test being positive if the subject has a disease relative to the odds of the test being positive if the subject does not have the disease.