Managing class imbalance in the training of a large language model to predict patient selection for total knee arthroplasty : Results from the Artificial intelligence to Revolutionise the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) project

Farrow, LukeAnderson, LesleyZhong, Mingjun2025-02-282025-02-282025-06Farrow, L, Anderson, L & Zhong, M 2025, 'Managing class imbalance in the training of a large language model to predict patient selection for total knee arthroplasty : Results from the Artificial intelligence to Revolutionise the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) project', Knee, vol. 54, pp. 1-8. https://doi.org/10.1016/j.knee.2025.02.0070968-0160RIS: urn:8BC40053134F7158B854879B42B45B9AORCID: /0000-0002-1525-1270/work/179300256ORCID: /0000-0002-1000-3649/work/179300144ORCID: /0000-0002-1443-5908/work/179748792https://hdl.handle.net/2164/25109The authors are grateful to the team at the Grampian Data Safe Haven for their assistance in access to the included data and to the CSO for funding the project.8597473engArtificial intelligenceNatural language processingLarge language modelKneeArthroplastyClass imbalanceR Medicine (General)R1Managing class imbalance in the training of a large language model to predict patient selection for total knee arthroplasty : Results from the Artificial intelligence to Revolutionise the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) projectJournal article10.1016/j.knee.2025.02.007https://www.sciencedirect.com/science/article/pii/S096801602500021354