17 citations · 53 across the 9 of their papers we have counts for
9 papers
Statistical Design and Analysis for Robust Machine Learning: A Case Study from COVID-19
Davide Pigoli, Kieran Baker, Jobie Budd +19
Since early in the coronavirus disease 2019 (COVID-19) pandemic, there has been interest in using artificial intelligence methods to predict COVID-19 infection status based on voca…
Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers
Harry Coppock, George Nicholson, Ivan Kiskin +22
Recent work has reported that AI classifiers trained on audio recordings can accurately predict severe acute respiratory syndrome coronavirus 2 (SARSCoV2) infection status. Here, w…
A large-scale and PCR-referenced vocal audio dataset for COVID-19
Jobie Budd, Kieran Baker, Emma Karoune +23
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 sympt…
Assessments and developments in constructing a National Health Index for policy making, in the United Kingdom
Anna Freni-Sterrantino, Thomas P Prescott, Greg Ceely +2
Composite indicators are a useful tool to summarize, measure and compare changes among different communities. The UK Office for National Statistics has created an annual England He…
Interoperability of statistical models in pandemic preparedness: principles and reality
George Nicholson, Marta Blangiardo, Mark Briers +12
We present "interoperability" as a guiding framework for statistical modelling to assist policy makers asking multiple questions using diverse datasets in the face of an evolving p…
Bayesian imputation of COVID-19 positive test counts for nowcasting under reporting lag
Radka Jersakova, James Lomax, James Hetherington +4
Obtaining up to date information on the number of UK COVID-19 regional infections is hampered by the reporting lag in positive test results for people with COVID-19 symptoms. In th…