ChatGPT can yield valuable responses in the context of orthopaedic trauma surgeryShow others and affiliations
2024 (English)In: Journal of Experimental Orthopaedics, ISSN 2197-1153, Vol. 11, no 3, article id e12047Article in journal (Refereed) Published
Abstract [en]
Purpose: To assess the possibility of using Generative Pretrained Transformer (ChatGPT) specifically in the context of orthopaedic trauma surgery by questions posed to ChatGPT and to evaluate responses (correctness, completeness and adaptiveness) by orthopaedic trauma surgeons.
Methods: ChatGPT (GPT-4 of 12 May 2023) was asked to address 34 common orthopaedic trauma surgery-related questions and generate responses suited to three target groups: patient, nonorthopaedic medical doctor and expert orthopaedic surgeon. Three orthopaedic trauma surgeons independently assessed ChatGPT's responses by using a three-point response scale with a response range between 0 and 2, where a higher number indicates better performance (correctness, completeness and adaptiveness).
Results: A total of 18 (52.9%) of all responses were assessed to be correct (2.0) for the patient target group, while 22 (64.7%) and 24 (70.5%) of the responses were determined to be correct for nonorthopaedic medical doctors and expert orthopaedic surgeons, respectively. Moreover, a total of 18 (52.9%), 25 (73.5%) and 28 (82.4%) of the responses were assessed to be complete (2.0) for patients, nonorthopaedic medical doctors and expert orthopaedic surgeons, respectively. The average adaptiveness was 1.93, 1.95 and 1.97 for patients, nonorthopaedic medical doctors and expert orthopaedic surgeons, respectively.
Conclusion: The study results indicate that ChatGPT can yield valuable and overall correct responses in the context of orthopaedic trauma surgery across different target groups, which encompassed patients, nonorthopaedic medical surgeons and expert orthopaedic surgeons. The average correctness scores, completeness levels and adaptiveness values indicated the ability of ChatGPT to generate overall correct and complete responses adapted to the target group.
Place, publisher, year, edition, pages
John Wiley & Sons, 2024. Vol. 11, no 3, article id e12047
Keywords [en]
AI, artificial intelligence, large language models, LLMs trauma orthopaedics
National Category
Orthopaedics
Identifiers
URN: urn:nbn:se:umu:diva-226624DOI: 10.1002/jeo2.12047ISI: 001248135000001PubMedID: 38887661Scopus ID: 2-s2.0-85196087885OAI: oai:DiVA.org:umu-226624DiVA, id: diva2:1873178
2024-06-192024-06-192024-06-24Bibliographically approved