An AI system for continuous knee osteoarthritis severity grading: An anomaly detection inspired approach with few labels
- DOI
- 10.1016/j.artmed.2025.103138
- Published
- 2025-09
- Container
- Artificial Intelligence in Medicine
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.artmed.2025.103138,
title = {An AI system for continuous knee osteoarthritis severity grading: An anomaly detection inspired approach with few labels},
author = {Niamh Belton and Aonghus Lawlor and Kathleen M. Curran},
year = {2025},
journal = {Artificial Intelligence in Medicine},
doi = {10.1016/j.artmed.2025.103138},
url = {https://doi.org/10.1016/j.artmed.2025.103138}
}RIS
TY - JOUR TI - An AI system for continuous knee osteoarthritis severity grading: An anomaly detection inspired approach with few labels AU - Niamh Belton AU - Aonghus Lawlor AU - Kathleen M. Curran PY - 2025 JO - Artificial Intelligence in Medicine DO - 10.1016/j.artmed.2025.103138 UR - https://doi.org/10.1016/j.artmed.2025.103138 ER -
APA
Belton, N., Lawlor, A., & Curran, K. M. (2025). An AI system for continuous knee osteoarthritis severity grading: An anomaly detection inspired approach with few labels. Artificial Intelligence in Medicine. https://doi.org/10.1016/j.artmed.2025.103138
Source records
- crossref · retrieved 2026-09-25T20:08:34.872Z