Forecasting regional COVID-19 hospitalisation in England using ordinal machine learning method
Accurate ordinal forecasts of COVID-19 hospitalisations were obtained using XGBoost and mobility data. While uniform ordinal levels showed higher apparent accuracy, we recommend n-tile ordinal levels which contain far richer information.
Authors
- Ruiyun Li (ORCID: https://orcid.org/0000-0001-8927-9965)
- Kin On Kwok (ORCID: https://orcid.org/0000-0002-2804-5433)
- Haowei Wang (ORCID: https://orcid.org/0000-0003-4753-8783)
- Steven Riley
Institutions
- Chinese University of Hong Kong (HK)
- NIHR Imperial Biomedical Research Centre (GB)
- Imperial College London (GB)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Epidemics
- Published
- 2025-09-12
- DOI
- https://doi.org/10.1016/j.epidem.2025.100856
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00