… This study aimed to develop a mortality risk prediction model for COVID-19 based on ML
algorithms … predictors of mortality among COVID-19 in-hospital patients? (2) What is the best ML …

… ability of various machine learning algorithms to predict clinical outcomes such as ICU
admission or mortality using data available from the initial ED encounter of COVID-19 patients. …

… algorithms used in relation to COVID-19. We focus on the potential of ML for two main
applications: diagnosis of COVID-19 and prediction of mortality … Aspects related to algorithm types, …

… Finally, we showed that unsupervised learning algorithms allow a global analysis of the
set of drugs administered to the patient population. This allowed us to automatically identify …

… whether it belonged to baseline ML or advanced DL algorithms. Since in literature there are
many implementable and customizable algorithms, we expected to find several and different …

Early prediction of patient mortality risks during a pandemic can decrease mortality by
assuring efficient resource allocation and treatment planning. This study aimed to develop and …

… Artificial intelligence techniques allow one to analyze large amounts of data to find hidden
… validate a mortality score at admission for COVID-19 based on high-level machine learning. …

… To compare the performances of various machine learning algorithms, we tried six different
models as listed below. The most optimum feature set was used as inputs to these models. …

… to share experience on COVID-19 patients’ treatment among … Finally, data on COVID-19
patients admitted to the COVID-19 … a machine learning approach for ICU mortality in COVID-19 …

… feasible machine-learning algorithm to stratify the mortality risk in a sample of patients
admitted to a COVID-19 referral center in the Veneto region, Italy, during the first COVID-19 wave. …