Selected article for: "AUC curve and discriminant analysis"

Author: changzheng wang; Chengbin Li
Title: Preliminary study to identify severe from moderate cases of COVID-19 using NLR&RDW-SD combination parameter
  • Document date: 2020_4_14
  • ID: jecsj3xw_14
    Snippet: Age was represented in median (range), and others demographics and clinical characteristics were expressed in frequency and percentage. The significance was tested by chi square or Fisher's exact test. The quantized variables of blood parameters were expressed as mean ± standard deviation. The significance between the two groups was tested by student's t-test. P<0.05 was considered statistically significant in all statistical analyses. Linear di.....
    Document: Age was represented in median (range), and others demographics and clinical characteristics were expressed in frequency and percentage. The significance was tested by chi square or Fisher's exact test. The quantized variables of blood parameters were expressed as mean ± standard deviation. The significance between the two groups was tested by student's t-test. P<0.05 was considered statistically significant in all statistical analyses. Linear discriminant analysis (LDA) was employed to perform linear combination of each two parameters and extract the best data features to distinguish moderate and severe cases of COVID-19 patients. The diagnostic values of valuable parameters for differential mild and severe cases of COVID-19 patients were assessed by receiver operating characteristic (ROC) and area under the ROC curve (AUC).

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