Effective Utilization of Data for Predicting COVID‐19 Dynamics: An Exploration through Machine Learning Models
D Chumachenko, T Dudkina, S Yakovlev… - … of Telemedicine and …, 2023 - Wiley Online Library
This study is centered around the COVID‐19 pandemic which has posed a global health
concern for over three years. It emphasizes the importance of effectively utilizing epidemic …
concern for over three years. It emphasizes the importance of effectively utilizing epidemic …
Prediction models for COVID-19 disease outcomes
SARS-CoV-2 has caused over 6.9 million deaths and continues to produce lasting health
consequences. COVID-19 manifests broadly from no symptoms to death. In a retrospective …
consequences. COVID-19 manifests broadly from no symptoms to death. In a retrospective …
Utilization of machine-learning models to accurately predict the risk for critical COVID-19
Among patients with Coronavirus disease (COVID-19), the ability to identify patients at risk
for deterioration during their hospital stay is essential for effective patient allocation and …
for deterioration during their hospital stay is essential for effective patient allocation and …
Machine learning, deep learning, and mathematical models to analyze forecasting and epidemiology of COVID-19: a systematic literature review
COVID-19 is a disease caused by SARS-CoV-2 and has been declared a worldwide
pandemic by the World Health Organization due to its rapid spread. Since the first case was …
pandemic by the World Health Organization due to its rapid spread. Since the first case was …
Forecasting the novel coronavirus COVID-19
F Petropoulos, S Makridakis - PloS one, 2020 - journals.plos.org
What will be the global impact of the novel coronavirus (COVID-19)? Answering this
question requires accurate forecasting the spread of confirmed cases as well as analysis of …
question requires accurate forecasting the spread of confirmed cases as well as analysis of …
[HTML][HTML] COVID-19 prediction models: a systematic literature review
SM Shakeel, NS Kumar, PP Madalli… - Osong public health …, 2021 - ncbi.nlm.nih.gov
As the world grapples with the problem of the coronavirus disease 2019 (COVID-19)
pandemic and its devastating effects, scientific groups are working towards solutions to …
pandemic and its devastating effects, scientific groups are working towards solutions to …
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 …
Risk factors associated with covid-19 lethality: A machine learning approach using Mexico database
A Carvantes-Barrera, L Díaz-González… - Journal of Medical …, 2023 - Springer
Identifying risk factors associated with COVID-19 lethality is crucial in combating the ongoing
pandemic. In this study, we developed lethality predictive models for each epidemiological …
pandemic. In this study, we developed lethality predictive models for each epidemiological …
[HTML][HTML] Machine learning approaches in COVID-19 diagnosis, mortality, and severity risk prediction: A review
N Alballa, I Al-Turaiki - Informatics in medicine unlocked, 2021 - Elsevier
The existence of widespread COVID-19 infections has prompted worldwide efforts to control
and manage the virus, and hopefully curb it completely. One important line of research is the …
and manage the virus, and hopefully curb it completely. One important line of research is the …
Development and validation of a web-based severe COVID-19 risk prediction model
SH Woo, AJ Rios-Diaz, AA Kubey… - The American Journal of …, 2021 - Elsevier
Abstract Background Coronavirus disease 2019 (COVID-19) carries high morbidity and
mortality globally. Identification of patients at risk for clinical deterioration upon presentation …
mortality globally. Identification of patients at risk for clinical deterioration upon presentation …