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Assessing the Performance of Machine Learning Methods Trained on Public Health Observational Data: A Case Study From COVID‐19.

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Title: Assessing the Performance of Machine Learning Methods Trained on Public Health Observational Data: A Case Study From COVID‐19.
Authors: Pigoli, Davide1,2 (AUTHOR) davide.pigoli@kcl.ac.uk, Baker, Kieran1,2 (AUTHOR), Budd, Jobie3 (AUTHOR), Butler, Lorraine4 (AUTHOR), Coppock, Harry2,5 (AUTHOR), Egglestone, Sabrina4 (AUTHOR), Gilmour, Steven G.1,2 (AUTHOR), Holmes, Chris2,6 (AUTHOR), Hurley, David4 (AUTHOR), Jersakova, Radka2 (AUTHOR), Kiskin, Ivan7 (AUTHOR), Koutra, Vasiliki1,2 (AUTHOR), Mellor, Jonathon4 (AUTHOR), Nicholson, George2,6 (AUTHOR), Packham, Joe4 (AUTHOR), Patel, Selina3,4 (AUTHOR), Payne, Richard4 (AUTHOR), Roberts, Stephen J.8 (AUTHOR), Schuller, Björn W.2,5 (AUTHOR), Tendero‐Cañadas, Ana4,9 (AUTHOR)
Source: Statistics in Medicine. 11/10/2024, Vol. 43 Issue 25, p4861-4871. 11p.
Database: Mathematics Source
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  Data: <searchLink fieldCode="JN" term="%22Statistics+in+Medicine%22">Statistics in Medicine</searchLink>. 11/10/2024, Vol. 43 Issue 25, p4861-4871. 11p.
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