Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal
Objective To review and appraise the validity and usefulness of published and preprint
reports of prediction models for prognosis of patients with covid-19, and for detecting people …
reports of prediction models for prognosis of patients with covid-19, and for detecting people …
Prognostic models in COVID-19 infection that predict severity: a systematic review
Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability
remains controversial. We performed a systematic review to summarize and critically …
remains controversial. We performed a systematic review to summarize and critically …
Coronavirus disease (COVID-19) cases analysis using machine-learning applications
Today world thinks about coronavirus disease that which means all even this pandemic
disease is not unique. The purpose of this study is to detect the role of machine-learning …
disease is not unique. The purpose of this study is to detect the role of machine-learning …
Explainable artificial intelligence (XAI) for predicting the need for intubation in methanol-poisoned patients: a study comparing deep and machine learning models
The need for intubation in methanol-poisoned patients, if not predicted in time, can lead to
irreparable complications and even death. Artificial intelligence (AI) techniques like machine …
irreparable complications and even death. Artificial intelligence (AI) techniques like machine …
The economics of deep and machine learning-based algorithms for COVID-19 prediction, detection, and diagnosis sha** the organizational management of …
Research background: Deep and machine learning-based algorithms can assist in COVID-
19 image-based medical diagnosis and symptom tracing, optimize intensive care unit …
19 image-based medical diagnosis and symptom tracing, optimize intensive care unit …
Machine learning methods to predict mechanical ventilation and mortality in patients with COVID-19
Background The Coronavirus disease 2019 (COVID-19) pandemic has affected millions of
people across the globe. It is associated with a high mortality rate and has created a global …
people across the globe. It is associated with a high mortality rate and has created a global …
[HTML][HTML] A novel explainable COVID-19 diagnosis method by integration of feature selection with random forest
Abstract Several Artificial Intelligence-based models have been developed for COVID-19
disease diagnosis. In spite of the promise of artificial intelligence, there are very few models …
disease diagnosis. In spite of the promise of artificial intelligence, there are very few models …
A comprehensive review of machine learning used to combat COVID-19
Coronavirus disease (COVID-19) has had a significant impact on global health since the
start of the pandemic in 2019. As of June 2022, over 539 million cases have been confirmed …
start of the pandemic in 2019. As of June 2022, over 539 million cases have been confirmed …
[HTML][HTML] A new COVID-19 intubation prediction strategy using an intelligent feature selection and K-NN method
Background Predicting severe respiratory failure due to COVID-19 can help triage patients
to higher levels of care, resource allocation and decrease morbidity and mortality. The need …
to higher levels of care, resource allocation and decrease morbidity and mortality. The need …
[HTML][HTML] Design of an artificial neural network to predict mortality among COVID-19 patients
M Shanbehzadeh, R Nopour… - Informatics in medicine …, 2022 - Elsevier
Introduction The fast pandemic of coronavirus disease 2019 (COVID-19) has challenged
clinicians with many uncertainties and ambiguities regarding disease outcomes and …
clinicians with many uncertainties and ambiguities regarding disease outcomes and …