Machine-learning models for predicting survivability in COVID-19 patients
ID Acheme, OR Vincent - Data Science for COVID-19, 2021 - Elsevier
COVID-19 is a disease currently ravaging the world, bringing unprecedented health and
economic challenges to several nations. There are presently close to five million reported …
economic challenges to several nations. There are presently close to five million reported …
[HTML][HTML] A machine learning-based model for survival prediction in patients with severe COVID-19 infection
L Yan, H Zhang, J Goncalves, Y Xiao, M Wang, Y Guo… - 2020 - europepmc.org
The sudden increase of COVID-19 cases is putting a high pressure on healthcare services
worldwide. At the current stage, fast, accurate and early clinical assessment of the disease …
worldwide. At the current stage, fast, accurate and early clinical assessment of the disease …
[HTML][HTML] Predicting mortality risk in patients with COVID-19 using machine learning to help medical decision-making
M Pourhomayoun, M Shakibi - Smart health, 2021 - Elsevier
In the wake of COVID-19 disease, caused by the SARS-CoV-2 virus, we designed and
developed a predictive model based on Artificial Intelligence (AI) and Machine Learning …
developed a predictive model based on Artificial Intelligence (AI) and Machine Learning …
An interpretable mortality prediction model for COVID-19 patients
The sudden increase in COVID-19 cases is putting high pressure on healthcare services
worldwide. At this stage, fast, accurate and early clinical assessment of the disease severity …
worldwide. At this stage, fast, accurate and early clinical assessment of the disease severity …
Prognostic machine learning models for COVID‐19 to facilitate decision making
An increasing number of COVID‐19 cases worldwide has overwhelmed the healthcare
system. Physicians are struggling to allocate resources and to focus their attention on high …
system. Physicians are struggling to allocate resources and to focus their attention on high …
Prognostic model of COVID-19 severity and survival among hospitalized patients using machine learning techniques
I Lodato, AV Iyer, IZ To, ZY Lai, HSY Chan… - Diagnostics, 2022 - mdpi.com
We conducted a statistical study and developed a machine learning model to triage COVID-
19 patients affected during the height of the COVID-19 pandemic in Hong Kong based on …
19 patients affected during the height of the COVID-19 pandemic in Hong Kong based on …
Predicting in-hospital mortality of patients with COVID-19 using machine learning techniques
F Tezza, G Lorenzoni, D Azzolina, S Barbar… - Journal of Personalized …, 2021 - mdpi.com
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 …
set of Machine Learning Techniques (MLTs), comparing their ability to predict the outcome …
Machine Learning‐Based Model to Predict the Disease Severity and Outcome in COVID‐19 Patients
The novel coronavirus (COVID‐19) outbreak produced devastating effects on the global
economy and the health of entire communities. Although the COVID‐19 survival rate is high …
economy and the health of entire communities. Although the COVID‐19 survival rate is high …
Comparing machine learning algorithms for predicting COVID-19 mortality
K Moulaei, M Shanbehzadeh… - BMC medical informatics …, 2022 - Springer
Background The coronavirus disease (COVID-19) hospitalized patients are always at risk of
death. Machine learning (ML) algorithms can be used as a potential solution for predicting …
death. Machine learning (ML) algorithms can be used as a potential solution for predicting …
A machine learning model for predicting deterioration of COVID-19 inpatients
O Noy, D Coster, M Metzger, I Atar… - Scientific reports, 2022 - nature.com
The COVID-19 pandemic has been spreading worldwide since December 2019, presenting
an urgent threat to global health. Due to the limited understanding of disease progression …
an urgent threat to global health. Due to the limited understanding of disease progression …