ArticleCureus2026
Artificial Intelligence in Orthopaedic Research: A Technical Report on Opportunities and Pitfalls.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence is transforming the landscape of orthopaedic research, offering tools that enhance data analysis, improve diagnostic workflows, and support personalized patient care. In recent years, AI applications in orthopaedics have expanded significantly, ranging from imaging-based fracture detection and musculoskeletal tumor classification to surgical planning, implant identification, and biomechanical gait analysis. Additionally, AI is being used in research-centric tasks, including outcome prediction modeling, literature screening, and preliminary manuscript drafting. This technical report presents a narrative technical review synthesizing emerging applications of AI within orthopaedic research based on recent PubMed-indexed studies from the past five years. We explore how machine learning and deep learning algorithms are being developed, validated, and deployed across various research domains. The report highlights the tangible benefits of AI, such as increased efficiency, diagnostic precision, and reproducibility of analysis. However, it also addresses the significant pitfalls, including reliance on limited or biased datasets, lack of model transparency, and unresolved ethical challenges. Of particular concern is the use of generative AI tools in scientific writing, which, while promising, raises questions about originality, accuracy, and research integrity. Overall, AI is poised to support, not replace, orthopaedic researchers. Successful integration will require robust validation, ethical safeguards, and continued collaboration between data scientists and clinical experts.
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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.