5 citations · 12 across the 7 of their papers we have counts for
7 papers
Influenza Hospitalisations in England during the 2022/23 Season: do different data sources drive divergence in modelled waves? A comparison of surveillance and administrative data
Jonathon Mellor, Rachel Christie, James Guilder +5
Accurate and representative data is vital for precisely reporting the impact of influenza in healthcare systems. Northern hemisphere winter 2022/23 experienced the most substantial…
Real-time COVID-19 hospital admissions forecasting with leading indicators and ensemble methods in England
Jonathon Mellor, Rachel Christie, Robert S Paton +6
Hospitalisations from COVID-19 with Omicron sub-lineages have put a sustained pressure on the English healthcare system. Understanding the expected healthcare demand enables more e…
Understanding the leading indicators of hospital admissions from COVID-19 across successive waves in the UK
Jonathon Mellor, Christopher E Overton, Martyn Fyles +4
Following the UK Government's Living with COVID-19 Strategy and the end of universal testing, hospital admissions are an increasingly important measure of COVID-19 pandemic pressur…
Forecasting influenza hospital admissions within English sub-regions using hierarchical generalised additive models
Jonathon Mellor, Rachel Christie, Christopher E Overton +5
Background: Seasonal influenza causes a substantial burden on healthcare services over the winter period when these systems are already under pressure. Policies during the COVID-19…
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…