ArticleDigital health
High-throughput digital cough recording on a university campus: A SARS-CoV-2-negative curated open database and operational template for acoustic screening of respiratory diseases.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Performance evaluation of human cough annotators: optimal metrics and sex differences.BMJ open respiratory research · 2023Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Respiratory illnesses have information-rich acoustic biomarkers, such as cough, that can potentially play an important role in screening populations for disease risk. To realize that potential, datasets of paired acoustic-clinical samples are needed for the development and validation of acoustic screening models, and protocols for collecting acoustic samples must be efficient and safe. We collected cough acoustic signatures at a high-throughput SARS-CoV-2 testing site on a college campus. Here, we share logistical details and the dataset of acoustic cough signatures paired with the gold standard in SARS-CoV-2 testing of SARS-CoV-2 genomic sequences using qRT-PCR. Methods: Cough recordings were collected in winter-spring 2021 at a rural residential college (Sewanee, TN, USA), where approximately 2000 students were tested for SARS-CoV-2 on a weekly basis. Cough collection was managed by student volunteers using custom software. Results: 4302 coughs were recorded from 960 participants over 11 weeks. All coughs were COVID-19 negative. Approximately 30 s were required to check-in a participant and collect their cough. Conclusion: The value of acoustic screening tools depends upon our ability to develop and implement them reliably and quickly. For that to happen, high-quality datasets and logistical insights must be collected and shared on an ongoing basis.
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