Objetivos: Crear una herramienta que permita predecir mortalidad en pacientes COVID-19
desde urgencias aplicando sistemas de aprendizaje automático (Machine Learning y Deep …

COVID-19 is responsible for high mortality, but robust machine learning-based predictors of
mortality are lacking. To generate a model for predicting mortality in patients hospitalized …

Background: COVID-19 infected millions of people and increased mortality worldwide.
Patients with suspected COVID-19 utilised emergency medical services (EMS) and attended …

The purpose of the study was to build a predictive model for estimating the risk of ICU
admission or mortality among patients hospitalized with COVID-19 and provide a user …

Rationale: Coronavirus disease 2019 (COVID-19) has caused significant death worldwide
despite public health measures such as lockdowns and vaccinations. Intensive care units …

The present work aims to identify the predictors of COVID-19 in-hospital mortality testing a
set of Machine Learning Techniques (MLTs), comparing their ability to predict the outcome …

Recently, global health has seen an increase in demand for assistance as a result of the
COVID-19 pandemic. This has prompted many researchers to conduct different studies …

Abstract Background and Aim: We aimed to propose a mortality risk prediction tool to
facilitate COVID-19 patient management and allocation for the frontline physician on …

Abstract In Coronavirus disease 2019 (COVID-19), early identification of patients with a high
risk of mortality can significantly improve triage, bed allocation, timely management, and …

Abstract Background and Aims Infection with Covid‐19 disease can lead to mortality in a
short time. Early prediction of the mortality during an epidemic disease can save patients' …