… The machine learning algorithm used in this study is the RF, which is an ensemble meta-estimator
constructed from several decision trees 58 . These trees were fitted to the data using …

… use machine learning to construct a model for the analysis of risk factors and prediction of
mortality among ICU patients with COVID-19. … , and the machine learning algorithm can identify …

… Abstract—The COVID-19 pandemic sparked our research interest to explore and design a
… through Machine Learning algorithms to determine risk and mortality of COVID-19 admitted …

… dimension reduction algorithms were used to … COVID-19 mortality utilizing unbiased
computational techniques and detected the most predictive clinical features. Their machine learning (…

… Both Random Forest and XGBoost are machine-learning algorithms based on tree-based …
Machine learning-based CT radiomics model for predicting hospital stay in patients with …

… machine learning algorithms have strong capabilities of prediction and classification in relation
to COVID19 … COVID-19-related mortality. In 2020, Santosh [15] studied the role of artificial …

… algorithm, aiming to verify the causal link between polluting emissions and COVID-19
deaths… between fine particulate matter and COVID-19 deaths happens through the process of …

… of choosing one machine learning (ML) algorithm to model … In this paper, we took a
semi-parametric (machine learning) … spread, number of cases, and deaths of COVID-19 in the US …

… Machine learning studies that focus on COVID-19 have been … to use federated learning, a
machine learning technique that … , to predict mortality in hospitalized patients with COVID-19 …

… whether a machine learning algorithm is capable of predicting mortality with reduced racial
… used to triage COVID-19 patients could widen existing racial disparities in COVID-19 [34], …