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Automatic detection and prediction of COVID-19 in cough audio signals using coronavirus herd immunity optimizer algorithm.
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January 2025
Department of Electronics and Communication Engineering, Sri Ramakrishna Institute of Technology, Coimbatore, Tamilnadu, India, 641010.
The global spread of COVID-19, particularly through cough symptoms, necessitates efficient diagnostic tools. COVID-19 patients exhibit unique cough sound patterns distinguishable from other respiratory conditions. This study proposes an advanced framework to detect and predict COVID-19 using deep learning from cough audio signals.
View Article and Find Full Text PDFGlobal urban activity changes from COVID-19 physical distancing restrictions.
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January 2025
Universities Space Research Association, Washington, DC, USA.
During the COVID-19 pandemic changes in human activity became widespread through official policies and organically in response to the virus's transmission, which in turn, impacted the environment and the economy. The pandemic has been described as a natural experiment that tested how social and economic disruptions impacted different components of the global Earth System. To move this beyond hypotheses, locally-resolved, globally-available measures of how, where, and when human activity changed are critically needed.
View Article and Find Full Text PDFLinking and GenBank to the National Clinical Cohort Collaborative.
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January 2025
Department of Biomedical Informatics University of Arkansas for Medical Sciences, College of Medicine Little Rock Arkansas USA.
Objective: This project demonstrates the feasibility of connecting medical imaging data and features, SARS-CoV-2 genome variants, with clinical data in the National Clinical Cohort Collaborative (N3C) repository to accelerate integrative research on detection, diagnosis, and treatment of COVID-19-related morbidities. The N3C curated a rich collection of aggregated and de-identified electronic health records (EHR) data of over 18 million patients, including 7.5 million COVID-positive patients, seen at hospitals across the United States.
View Article and Find Full Text PDFPredicting work ability impairment in post COVID-19 patients: a machine learning model based on clinical parameters.
Infection
January 2025
Department of Medicine II, LMU University Hospital, LMU Munich, Munich, Germany.
The Post COVID-19 condition (PCC) is a complex disease affecting health and everyday functioning. This is well reflected by a patient's inability to work (ITW). In this study, we aimed to investigate factors associated with ITW (1) and to design a machine learning-based model for predicting ITW (2) twelve months after baseline.
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