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Titel:

A large-scale and PCR-referenced vocal audio dataset for COVID-19.

Dokumenttyp:
Dataset; Journal Article
Autor(en):
Budd, Jobie; Baker, Kieran; Karoune, Emma; Coppock, Harry; Patel, Selina; Payne, Richard; Tendero Cañadas, Ana; Titcomb, Alexander; Hurley, David; Egglestone, Sabrina; Butler, Lorraine; Mellor, Jonathon; Nicholson, George; Kiskin, Ivan; Koutra, Vasiliki; Jersakova, Radka; McKendry, Rachel A; Diggle, Peter; Richardson, Sylvia; Schuller, Björn W; Gilmour, Steven; Pigoli, Davide; Roberts, Stephen; Packham, Josef; Thornley, Tracey; Holmes, Chris
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 respiratory symptoms using vocal audio. The UK Health Security Agency recruited voluntary participants through the national Test and Trace programme and the REACT-1 survey in England from March 2021 to March 2022, during dominant transmission of the Alpha and Delta SARS-CoV-2 variants and some Omicron variant sublineages. Audio recordi...     »
Zeitschriftentitel:
Sci Data
Jahr:
2024
Band / Volume:
11
Heft / Issue:
1
Volltext / DOI:
doi:10.1038/s41597-024-03492-w
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/38937483
TUM Einrichtung:
Lehrstuhl für Health Informatics (Prof. Schuller)
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