Assessing the performance of machine learning methods trained on public health observational data: a case study from COVID-19

DOI10.1002/sim.10211MaRDI QIDQ6663852

Lorraine Butler, Ana Tendero-Cañadas, Jobie Budd, Jonathon Mellor, David Hurley, Alexander Titcomb, Steven G. Gilmour, Radka Jersakova, Tracey Thornley, Selina Patel, Sabrina Egglestone, Joe Packham, Ivan Kiskin, Björn W. Schuller, Vasiliki Koutra, Richard D. Payne, Kieran Baker, Stephen J. Roberts, Christopher C. Holmes, Davide Pigoli, Harry Coppock, George Nicholson

Publication date: 15 January 2025

Published in: Statistics in Medicine (Search for Journal in Brave)

zbMATH Keywords

matchingconfoundingbioacoustic markerschoice of test setUK COVID-19 vocal audio dataset

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

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