ICU Admission Prediction Using Machine Learning for Covid-19 Patients

A machine learning and explainable artificial intelligence triage-prediction system for COVID-19

“…RF achieved high Recall and F-1 scores of 97% and 91%, respectively. However, Xgboost gave higher accuracy, precision, and AUC scores approximating 97%, 97%, 96%, and 96%, respectively, compared to the RF classifier [40] .…”

Machine Learning-Driven Prediction of ICU Admissions for COVID-19 Patients

“…Subudhi et al [28] made the prediction model with an RF classifier with important markers such as CRP, most clinical blood results, oxygen level, chloride, D-dimer, and procalcitonin. According to the papers [32,57], the XGB algorithm predicts better and has an AUC of 0.98 and 0.83, respectively. High albumin present in the body can also factor in ICU admittance [58].…”