Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU.

ABSTRACT: Rationale: Given the expanding number of COVID-19 cases and the potential for new waves of infection, there is an urgent need for early prediction of the severity of the disease in intensive care unit (ICU) patients to optimize treatment strategies. Objectives: Early prediction of mortality using machine learning based on typical laboratory results and clinical data registered on the day of ICU admission. Methods: We retrospectively studied 797 patients diagnosed with COVID-19 in Iran and the United Kingdom (U.K.). To find parameters with the highest predictive values, Kolmogorov-Smirnov and Pearson chi-squared tests were used. Several machine learning algorithms, including Random Forest (RF), logistic regression, gradient boosting classifier, support vector machine cl

SUBMITTER: Jamshidi E 

PROVIDER: S-EPMC8792458 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature