Predicting the disease outcome in COVID-19 positive patients through Machine Learning: a retrospective cohort study with Brazilian data
FSH De Souza, NS Hojo-Souza… - Frontiers in Artificial …, 2021 - frontiersin.org
The first officially registered case of COVID-19 in Brazil was on February 26, 2020. Since
then, the situation has worsened with more than 672, 000 confirmed cases and at least 36 …
then, the situation has worsened with more than 672, 000 confirmed cases and at least 36 …
Machine learning-based ensemble approach for predicting the mortality risk of COVID-19 patients: a case study
K Kumar - Intelligent Data Analysis for COVID-19 Pandemic, 2021 - Springer
Recent outbreak of the COVID-19 pandemic in December 2019 has witnessed a rapid
spread from Wuhan, China, to all over the world. This highly transmittable infectious disease …
spread from Wuhan, China, to all over the world. This highly transmittable infectious disease …
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 classification approach for predicting COVID-19 Patient's survival outcome with machine learning techniques
COVID-19 is an infectious disease discovered after the outbreak began in Wuhan, China, in
December 2019. COVID-19 is still becoming an increasing global threat to public health …
December 2019. COVID-19 is still becoming an increasing global threat to public health …
[HTML][HTML] Predicting prognosis in COVID-19 patients using machine learning and readily available clinical data
TW Campbell, MP Wilson, H Roder… - International journal of …, 2021 - Elsevier
Rationale: Prognostic tools for aiding in the treatment of hospitalized COVID-19 patients
could help improve outcome by identifying patients at higher or lower risk of severe disease …
could help improve outcome by identifying patients at higher or lower risk of severe disease …
Machine learning assisted prediction of prognostic biomarkers associated with COVID-19, using clinical and proteomics data
With the availability of COVID-19-related clinical data, healthcare researchers can now
explore the potential of computational technologies such as artificial intelligence (AI) and …
explore the potential of computational technologies such as artificial intelligence (AI) and …
Learning accurate personalized survival models for predicting hospital discharge and mortality of COVID-19 patients
Since it emerged in December of 2019, COVID-19 has placed a huge burden on medical
care in countries throughout the world, as it led to a huge number of hospitalizations and …
care in countries throughout the world, as it led to a huge number of hospitalizations and …
Predicting COVID-19 mortality with electronic medical records
H Estiri, ZH Strasser, JG Klann, P Naseri… - NPJ digital …, 2021 - nature.com
This study aims to predict death after COVID-19 using only the past medical information
routinely collected in electronic health records (EHRs) and to understand the differences in …
routinely collected in electronic health records (EHRs) and to understand the differences in …
Early outcome detection for COVID-19 patients
With the outbreak of COVID-19 exerting a strong pressure on hospitals and health facilities,
clinical decision support systems based on predictive models can help to effectively improve …
clinical decision support systems based on predictive models can help to effectively improve …
Do not forget interaction: Predicting fatality of COVID-19 patients using logistic regression
Amid the ongoing COVID-19 pandemic, whether COVID-19 patients with high risks can be
recovered or not depends, to a large extent, on how early they will be treated appropriately …
recovered or not depends, to a large extent, on how early they will be treated appropriately …