Primary care prediction of hip and knee replacement 1–5 years in advance using Temporal Graph-based Convolutional Neural Networks (TG-CNNs)
Hip and knee replacement risk can be predicted up to 5 years in advance, with a temporal-graph based artificial intelligence model achieving the best performance. This may be used for planning preventative treatment or triaging patients.
Authors
- Sarah R. Kingsbury (ORCID: https://orcid.org/0000-0002-9917-1269)
- Zoe Hancox (ORCID: https://orcid.org/0000-0003-0473-5971)
- Samuel D. Relton (ORCID: https://orcid.org/0000-0003-0634-4587)
- Philip G. Conaghan (ORCID: https://orcid.org/0000-0002-3478-5665)
Institutions
- University of Leeds (GB)
- University of Bradford (GB)
- Nonwovens Innovation & Research Institute (GB)
- NIHR Leeds Musculoskeletal Biomedical Research Unit (GB)
Publication Details
- Journal
- Lara D. Veeken
- Published
- 2025-04-03
- DOI
- https://doi.org/10.1093/rheumatology/keaf185
- Citations
- 1
- Primary Topic
- Chronic Disease Management Strategies
- Type
- article
- Field-Weighted Citation Impact
- 1.35