[HTML][HTML] Prognostic models in COVID-19 infection that predict severity: a systematic review
Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability
remains controversial. We performed a systematic review to summarize and critically …
remains controversial. We performed a systematic review to summarize and critically …
Machine and deep learning methods for clinical outcome prediction based on physiological data of COVID-19 patients: a scoping review
Introduction Since the beginning of the COVID-19 pandemic, numerous machine and deep
learning (MDL) methods have been proposed in the literature to analyze patient …
learning (MDL) methods have been proposed in the literature to analyze patient …
[HTML][HTML] Using machine learning in prediction of ICU admission, mortality, and length of stay in the early stage of admission of COVID-19 patients
S Saadatmand, K Salimifard, R Mohammadi… - Annals of Operations …, 2023 - Springer
The recent COVID-19 pandemic has affected health systems across the world. Especially,
Intensive Care Units (ICUs) have played a pivotal role in the treatment of critically-ill patients …
Intensive Care Units (ICUs) have played a pivotal role in the treatment of critically-ill patients …
Artificial intelligence and discrete-event simulation for capacity management of intensive care units during the Covid-19 pandemic: a case study
The Covid-19 pandemic has pushed the Intensive Care Units (ICUs) into significant
operational disruptions. The rapid evolution of this disease, the bed capacity constraints, the …
operational disruptions. The rapid evolution of this disease, the bed capacity constraints, the …
[HTML][HTML] Improving intensive care unit early readmission prediction using optimized and explainable machine learning
JA González-Nóvoa, S Campanioni, L Busto… - International Journal of …, 2023 - mdpi.com
It is of great interest to develop and introduce new techniques to automatically and efficiently
analyze the enormous amount of data generated in today's hospitals, using state-of-the-art …
analyze the enormous amount of data generated in today's hospitals, using state-of-the-art …
[HTML][HTML] Machine learning first response to COVID-19: A systematic literature review of clinical decision assistance approaches during pandemic years from 2020 to …
G Badiola-Zabala, JM Lopez-Guede, J Estevez… - Electronics, 2024 - mdpi.com
Background: The declaration of the COVID-19 pandemic triggered global efforts to control
and manage the virus impact. Scientists and researchers have been strongly involved in …
and manage the virus impact. Scientists and researchers have been strongly involved in …
[HTML][HTML] Machine learning algorithm to predict acidemia using electronic fetal monitoring recording parameters
J Esteban-Escaño, B Castán, S Castán… - Entropy, 2021 - mdpi.com
Background: Electronic fetal monitoring (EFM) is the universal method for the surveillance of
fetal well-being in intrapartum. Our objective was to predict acidemia from fetal heart signal …
fetal well-being in intrapartum. Our objective was to predict acidemia from fetal heart signal …
ICU admission and mortality classifiers for COVID-19 patients based on subgroups of dynamically associated profiles across multiple timepoints
Abstract The coronavirus disease 2019 (COVID-19) which is caused by severe acute
respiratory syndrome coronavirus type 2 (SARS-CoV-2) is consistently causing profound …
respiratory syndrome coronavirus type 2 (SARS-CoV-2) is consistently causing profound …
[HTML][HTML] A multistate model and its standalone tool to predict hospital and ICU occupancy by patients with COVID-19
M Lafuente, FJ López, PM Mateo, AC Cebrián, J Asín… - Heliyon, 2023 - cell.com
Objective This study aims to build a multistate model and describe a predictive tool for
estimating the daily number of intensive care unit (ICU) and hospital beds occupied by …
estimating the daily number of intensive care unit (ICU) and hospital beds occupied by …
[HTML][HTML] Developing a decision model to early predict ICU admission for COVID-19 patients: A machine learning approach
Emergency department (ED) overcrowding is a significant problem in the US. This paper
develops a decision model to mitigate ED overcrowding by helping hospitals proactively …
develops a decision model to mitigate ED overcrowding by helping hospitals proactively …