Machine learning first response to COVID-19: A systematic literature review of clinical decision assistance approaches during pandemic years from 2020 to 2022
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 …
Early prediction of COVID-19 outcome using artificial intelligence techniques and only five laboratory indices
We aimed to develop a prediction model for intensive care unit (ICU) hospitalization of
Coronavirus disease-19 (COVID-19) patients using artificial neural networks (ANN). We …
Coronavirus disease-19 (COVID-19) patients using artificial neural networks (ANN). We …
Prediction of low pulse oxygen saturation in COVID-19 using remote monitoring post hospital discharge
Background Monitoring systems have been developed during the COVID-19 pandemic
enabling clinicians to remotely monitor physiological measures including pulse oxygen …
enabling clinicians to remotely monitor physiological measures including pulse oxygen …
Prediction of mortality risk and duration of hospitalization of COVID-19 patients with chronic comorbidities based on machine learning algorithms
Background The severity of coronavirus (COVID-19) in patients with chronic comorbidities is
much higher than in other patients, which can lead to their death. Machine learning (ML) …
much higher than in other patients, which can lead to their death. Machine learning (ML) …
Prognosis of COVID-19 severity using DERGA, a novel machine learning algorithm
It is important to determine the risk for admission to the intensive care unit (ICU) in patients
with COVID-19 presenting at the emergency department. Using artificial neural networks, we …
with COVID-19 presenting at the emergency department. Using artificial neural networks, we …
Using machine learning to identify patient characteristics to predict mortality of in-patients with COVID-19 in south Florida
Introduction The SARS-CoV-2 (COVID-19) pandemic has created substantial health and
economic burdens in the US and worldwide. As new variants continuously emerge …
economic burdens in the US and worldwide. As new variants continuously emerge …
[HTML][HTML] Machine learning for anxiety and depression profiling and risk assessment in the aftermath of an emergency
Background & objectives Mental health disorders pose an increasing public health
challenge worsened by the COVID-19 pandemic. The pandemic highlighted gaps in …
challenge worsened by the COVID-19 pandemic. The pandemic highlighted gaps in …
Machine and deep learning algorithms for COVID-19 mortality prediction using clinical and radiomic features
Aim: Machine learning (ML) and deep learning (DL) predictive models have been employed
widely in clinical settings. Their potential support and aid to the clinician of providing an …
widely in clinical settings. Their potential support and aid to the clinician of providing an …
[HTML][HTML] Feature Identification Using Interpretability Machine Learning Predicting Risk Factors for Disease Severity of In-Patients with COVID-19 in South Florida
Objective: The objective of the study was to establish an AI-driven decision support system
by identifying the most important features in the severity of disease for I ntensive C are U nit …
by identifying the most important features in the severity of disease for I ntensive C are U nit …
KLRB1 expression in nasopharyngeal mucosa as a prognostic biomarker in COVID-19 patients
M García-Aranda, MÁ Onieva, D Martín-García… - Scientific Reports, 2025 - nature.com
The resurgence of COVID-19 and the rise in severe outcomes emphasize the need for
reliable prognostic markers to guide patient care and optimize ICU and hospital resources …
reliable prognostic markers to guide patient care and optimize ICU and hospital resources …