Selected article for: "AUC ROC curve and operating characteristic"
Author: Rafael R. de Assis; Aarti Jain; Rie Nakajima; Algis Jasinskas; Jiin Felgner; Joshua M. Obiero; Oluwasanmi Adenaiye; Sheldon Tai; Filbert Hong; Philip Norris; Mars Stone; Graham Simmons; Anil Bagri; Martin Schreiber; Andreas Buser; Andreas Holbro; Manuel Battegay; Donald K. Milton; Huw Davies; Laurence M. Corash; Michael P. Busch; Philip L. Felgner; Saahir Khan
Title: Analysis of SARS-CoV-2 Antibodies in COVID-19 Convalescent Plasma using a Coronavirus Antigen Microarray
  • Document date: 2020_4_17
    • ID: ax9btc74_12
    Snippet: Each coronavirus antigen was evaluated for performance in discriminating the positive group from the negative group across a full range of assay cutoff values to generate Receiver Operating Characteristic (ROC) curves for which Area Under Curve (ROC AUC) was measured (Figure 4 ). High-performing antigens for detection of IgG or IgA defined by ROC AUC > 0.95 included all SARS-CoV-2 antigens and MERS-CoV S2 for IgG and SARS-CoV-2 S2 and S1+S2 for I.....
    Document: Each coronavirus antigen was evaluated for performance in discriminating the positive group from the negative group across a full range of assay cutoff values to generate Receiver Operating Characteristic (ROC) curves for which Area Under Curve (ROC AUC) was measured (Figure 4 ). High-performing antigens for detection of IgG or IgA defined by ROC AUC > 0.95 included all SARS-CoV-2 antigens and MERS-CoV S2 for IgG and SARS-CoV-2 S2 and S1+S2 for IgA ( Table 2 ). Each of these antigens discriminated between the positive group and the negative group with high significance ( Figure 5 ).

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