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ROC curves are used to evaluate the accuracy of markers for disease detection or prognosis. They provide a graphical means of comparing one or many continuous markers to a binary measure of disease, allowing determination of an optimal marker cutoff for positivity. Dr. Amalia Magaret from the University of Washington presents recent adaptations to the standard ROC curves, allowing for consideration of cost, inclusion of additional predictors of disease, and comparison and combination of predictive markers. Dr. Margaret Pepe in the department of biostatistics at the University of Washington developed many of these advances. (Series: Laboratory Medicine Grand Rounds)
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Beyond ROC Curves: Recent Statistical Advances in the Evaluation of Diagnostic and Prognostic Tests

ROC curves are used to evaluate the accuracy of... (更多)
頻道:iTunes 分類:科學 點擊:5
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