Using logistic regression to develop a diagnostic model for COVID-19: A single-center study.

Both models showed good fit, low mean square errors, and all parameters were highly significant.[ 20 ] Hu and Li showed that the AUC, sensitivity, and specificity of a death prediction model based on a logistic regression model for predicting the mortality of COVID-19 cases during hospitalization were 0.804, 83.8%, and 82.3%.[ 30 ] The novelty of this study lies in the use of logistic regression in developing a diagnostic model, it is extremely vital to develop an accurate diagnostic model that can effectively diagnose COVID-19 patients with important prognostic criteria.

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