ArticleArthroplasty today2024
AI-Generated Graduate Medical Education Content for Total Joint Arthroplasty: Comparing ChatGPT Against Orthopaedic Fellows.
Article in Arthroplasty today, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- The application of large language models in orthopedic postgraduate education: potentials, challenges, and future prospects.Journal of orthopaedic surgery and research · 2026Review
- Beyond acceptance: bounded use of AI and VR in orthopedic education.Frontiers in medicine · 2026Article
- Artificial Intelligence in Orthopaedic Education Across the Career Continuum: Moving from Benchmark Performance to Continuing Professional Development.Journal of CME · 2026Review
- Revolutionizing patient care: assessing ai-created discharge education for total hip replacement patients.BMC medical education · 2025Article
- Exploring ChatGPT's Efficacy in Orthopaedic Arthroplasty Questions Compared to Adult Reconstruction Surgeons.Arthroplasty today · 2025Article
- Large language models in orthopedics: An exploratory research trend analysis and machine learning classification.Journal of orthopaedics · 2025Article
- Review
- AI-Generated Graduate Medical Education Content for Total Joint Arthroplasty: Comment.Arthroplasty today · 2024Article
- Generative artificial intelligence in graduate medical education.Frontiers in medicine · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) in medicine has primarily focused on diagnosing and treating diseases and assisting in the development of academic scholarly work. This study aimed to evaluate a new use of AI in orthopaedics: content generation for professional medical education. Quality, accuracy, and time were compared between content created by ChatGPT and orthopaedic surgery clinical fellows. Methods: ChatGPT and 3 orthopaedic adult reconstruction fellows were tasked with creating educational summaries of 5 total joint arthroplasty-related topics. Responses were evaluated across 5 domains by 4 blinded reviewers from different institutions who are all current or former total joint arthroplasty fellowship directors or national arthroplasty board review course directors. Results: ChatGPT created better orthopaedic content than fellows when mean aggregate scores for all 5 topics and domains were compared (P ≤ .001). The only domain in which fellows outperformed ChatGPT was the integration of key points and references ( Conclusions: With its efficient and accurate content generation, the current findings underscore ChatGPT's potential as an adjunctive tool to enhance orthopaedic arthroplasty graduate medical education. Future studies are warranted to explore AI's role further and optimize its utility in augmenting the educational development of arthroplasty trainees.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.