ArticleJSES international2026
A focused PubMed artificial intelligence search program creates better literature reviews than general purpose artificial intelligence and is comparable to trainees in shoulder and elbow surgery.
Article in JSES international, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Background: As the use of artificial intelligence (AI) expands into orthopedic surgery, the potential to use AI for review and summation of literature leaves researchers and clinicians questioning the quality of AI-driven literature reviews. This study aims to compare AI-generated literature reviews to those done by orthopedic surgery trainees. Methods: ChatGPT-4o and The-Literature, a directed AI platform, were asked to produce a literature review on 5 shoulder and elbow-related research topics. The primary output produced by ChatGPT-4, The-Literature, a fourth-year medical student, a third-year orthopedic surgery resident, and an orthopedic surgery sports medicine fellow were blinded then graded on a 1-5 Likert Scale for evidence and analysis, conclusion, references, and overall quality by 2 fellowship-trained orthopedic shoulder and elbow surgeons. Results: The average overall Likert ratings were 2.90 ± 0.88 for the medical student, 3.90 ± 0.74 for the resident, 3.50 ± 0.53 for the fellow, 2.30 ± 1.16 for ChatGPT-4, and 3.40 ± 0.84 for The-Literature. The resident and fellow reviews were significantly better than ChatGPT-4 ( Conclusion: A limited and directed AI search program was comparable to orthopedic surgery trainees and performed better than an open AI large language model. ChatGPT-4 had poor overall utility stemming mainly from its tendency to fabricate references.
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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.