Selected article for: "accuracy specificity and logistic regression"
Author: Xiang Bai; Cong Fang; Yu Zhou; Song Bai; Zaiyi Liu; Qianlan Chen; Yongchao Xu; Tian Xia; Shi Gong; Xudong Xie; Dejia Song; Ronghui Du; Chunhua Zhou; Chengyang Chen; Dianer Nie; Dandan Tu; Changzheng Zhang; Xiaowu Liu; Lixin Qin; Weiwei Chen
Title: Predicting COVID-19 malignant progression with AI techniques
  • Document date: 2020_3_23
    • ID: 50oy9qqy_13
    Snippet: AUC, accuracy, specificity, and sensitivity were compared among different AI methods and multivariable logistic regression. Two-sided 95% CIs were used to summarize the sample variability in the estimates. Specifically, the normal approximation CIs was used for accuracy, sensitivity, and specificity. The CI for the AUC was estimated using the bootstrap method with 2000 replications......
    Document: AUC, accuracy, specificity, and sensitivity were compared among different AI methods and multivariable logistic regression. Two-sided 95% CIs were used to summarize the sample variability in the estimates. Specifically, the normal approximation CIs was used for accuracy, sensitivity, and specificity. The CI for the AUC was estimated using the bootstrap method with 2000 replications.

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