People with COVID-19 can experience impairing symptoms that require enhanced
surveillance. Our objective was to train an artificial intelligence-based model to predict the …

Many virological tests have been implemented during the Coronavirus Disease 2019
(COVID-19) pandemic for diagnostic purposes, but they appear unsuitable for screening …

Background Recent work has shown the potential of using audio data (eg, cough, breathing,
and voice) in the screening for COVID-19. However, these approaches only focus on one-off …

To identify Coronavirus disease (COVID-19) cases efficiently, affordably, and at scale, recent
work has shown how audio (including cough, breathing and voice) based approaches can …

Recently deep learning has attained a breakthrough in model accuracy for the classification
of images due mainly to convolutional neural networks. In the present study, we attempted to …

With the COVID-19 pandemic, several research teams have reported successful advances
in automated recognition of COVID-19 by voice. Resulting voice-based screening tools for …

COVID-19 cases are exponentially increasing worldwide; however, its clinical phenotype
remains unclear. Natural language processing (NLP) and machine learning approaches …

Abstract The UK COVID-19 Vocal Audio Dataset is designed for the training and evaluation
of machine learning models that classify SARS-CoV-2 infection status or associated …

Background Vocal biomarker–based machine learning approaches have shown promising
results in the detection of various health conditions, including respiratory diseases, such as …

Background: The COVID-19 pandemic has resulted in enormous costs to our society.
Besides finding medicines to treat those infected by the virus, it is important to find effective …