COVID-19 Mortality Risk Prediction using Clinical and Laboratory Examination: Machine Learning Approach for Implementation
SS Barough, SAA Safavi-Naini, F Siavoshi, A Tamimi… - 2022 - researchsquare.com
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 …
facilitate COVID-19 patient management and allocation for the frontline physician on …
Generalizable machine learning approach for COVID-19 mortality risk prediction using on-admission clinical and laboratory features
We aimed to propose a mortality risk prediction model using on-admission clinical and
laboratory predictors. We used a dataset of confirmed COVID-19 patients admitted to three …
laboratory predictors. We used a dataset of confirmed COVID-19 patients admitted to three …
[HTML][HTML] Accuracy of machine learning models to predict mortality in COVID-19 infection using the clinical and laboratory data at the time of admission
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 …
coronavirus disease 2019 (COVID-19) from the basic medical data on the first day of …
Comparison of two statistical models for predicting mortality in COVID-19 patients in Iran
Background: Today, the COVID-19 pandemic is ever-increasingly challenging healthcare
systems globally with many uncertainties and ambiguities regarding disease behavior and …
systems globally with many uncertainties and ambiguities regarding disease behavior and …
Predicting the mortality of patients with Covid‐19: A machine learning approach
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' …
short time. Early prediction of the mortality during an epidemic disease can save patients' …
Predicting the COVID‐19 mortality among Iranian patients using tree‐based models: A cross‐sectional study
A Aghakhani, J Shoshtarian Malak… - Health Science …, 2023 - Wiley Online Library
Abstract Background and Aims To explore the use of different machine learning models in
prediction of COVID‐19 mortality in hospitalized patients. Materials and Methods A total of …
prediction of COVID‐19 mortality in hospitalized patients. Materials and Methods A total of …
Multivariable mortality risk prediction using machine learning for COVID-19 patients at admission (AICOVID)
S Kar, R Chawla, SP Haranath, S Ramasubban… - Scientific reports, 2021 - nature.com
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 …
risk of mortality can significantly improve triage, bed allocation, timely management, and …
Predicting mortality in SARS-COV-2 (COVID-19) positive patients in the inpatient setting using a novel deep neural network
Background The nextwave of COVID-19 pandemic is anticipated to be worse than the initial
one and will strain the healthcare systems even more during the winter months. Our aim was …
one and will strain the healthcare systems even more during the winter months. Our aim was …
[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 …
Predict In-Hospital Mortality in COVID-19 Patients with a Machine Learning Webpage Tool Based on Clinical Laboratory Data: An Exploratory Research
Y Wang, J Zhan, F Zhang, J Cheng, J Li - 2024 - researchsquare.com
Background The death risk induced by COVID-19 posed tremendous pressure on medical
services, resulting in a shortage of critical care resources and a heavy disease burden …
services, resulting in a shortage of critical care resources and a heavy disease burden …
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