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The precise prediction of COVID‐19 prognosis remains a clinical challenge. In this regard, early identification of severe cases facilitates the triage and management of COVID‐19 cases. The present paper aims to explore the prognosis of COVID‐19 patients based on routine laboratory tests taken when patients are admitted.

A data set including 1455 COVID‐19 patients (727 male, 728 female) and their routine laboratory tests conducted upon hospital admission, age, Intensive Care Unit (ICU) admission, and outcome were gathered. The data set was randomly split into the train (75% of the data) and test data set (25% of the data). The explainable boosting machine (EBM) and extreme gradient boosting (XGBoost) were used for predicting the mortality and ICU admission of COVID‐19 cases. Also, feature importance was extracted using EBM and XGBoost.

The EBM and …