Selected article for: "area ROC curve and AUC ROC curve"
Author: Ria Lassaunière; Anders Frische; Zitta B Harboe; Alex CY Nielsen; Anders Fomsgaard; Karen A Krogfelt; Charlotte S Jørgensen
Title: Evaluation of nine commercial SARS-CoV-2 immunoassays
  • Document date: 2020_4_10
    • ID: 8cg5yj20_8
    Snippet: Sensitivity was defined as the proportion of patients correctly identified as having SARS-CoV-2 infections, as initially diagnosed using nucleic acid detection of SARS-CoV-2 in respiratory samples. Specificity was defined as the proportion of SARS-CoV-2 immune naïve study participants accurately identified as negative for COVID-19. The clinical accuracies of the ELISA assays were examined by using Receiver Operator Characteristic (ROC) plots wit.....
    Document: Sensitivity was defined as the proportion of patients correctly identified as having SARS-CoV-2 infections, as initially diagnosed using nucleic acid detection of SARS-CoV-2 in respiratory samples. Specificity was defined as the proportion of SARS-CoV-2 immune naïve study participants accurately identified as negative for COVID-19. The clinical accuracies of the ELISA assays were examined by using Receiver Operator Characteristic (ROC) plots with GraphPad Prism version 8.0.2 (GraphPad Software, San Diego, CA, USA). ROC area under the curve (AUC) were calculated as the fraction "correctly identified to be positive" and the fraction "falsely identified to be positive" determined according to manufacturer cut-off values for positive results.

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