L Verzellesi, A Botti, M Bertolini, V Trojani, G Carlini… - Electronics, 2023 - mdpi.com
Aim: Machine learning (ML) and deep learning (DL) predictive models have been employed widely in clinical settings. Their potential support and aid to the clinician of providing an …
AB García-Ruano, S García-Chileme… - Revista Española de …, 2021 - ojs.sanidad.gob.es
Fundamentos: La pandemia por COVID-19 ha generado una alta demanda de recursos hospitalarios llevando al límite al sistema nacional de salud. Es por ello que para reducir …
D Andrade-Girón, E Carreño-Cisneros… - Salud, Ciencia y …, 2023 - revista.saludcyt.ar
El brote de la enfermedad por coronavirus (COVID-19) ha infectado a millones de personas, ocasionando una elevada tasa de mortalidad en todo el mundo. Los pacientes con …
COVID-19 disease caused by the virus SARS-CoV2 appeared in Wuhan China in 2019, in March 11th 2020 it was declared a global pandemics, taking by March 2022 over 5,783,700 …
Objetivo: proponer una escala pronóstica para estratificar a los pacientes con neumonía viral por COVID-19 en los servicios de urgencias de los hospitales de segundo nivel …
E Chimbunde, LN Sigwadhi, JL Tamuzi… - Frontiers in Artificial …, 2023 - frontiersin.org
Background COVID-19 has strained healthcare resources, necessitating efficient prognostication to triage patients effectively. This study quantified COVID-19 risk factors and …
Aim This study aimed to develop a predictive model to predict patients' mortality with coronavirus disease 2019 (COVID-19) from the basic medical data on the first day of …
Since its emergence in late 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic with more than 55 million reported cases and 1.3 …
Background Several models have been developed to predict mortality in patients with COVID-19 pneumonia, but only a few have demonstrated enough discriminatory capacity …