ReviewAnnals of joint2025
Artificial intelligence in orthopaedic education: a narrative review.
Review in Annals of joint, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Review
- Are We Training Surgeons or Supervisors? Artificial Intelligence, Automation, and the Future of Surgical Expertise in Orthopedics.The archives of bone and joint surgery · 2026Article
- Artificial Intelligence in Orthopaedic Education Across the Career Continuum: Moving from Benchmark Performance to Continuing Professional Development.Journal of CME · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Objective: The integration of artificial intelligence (AI) into medical education is reshaping traditional learning paradigms. In orthopaedic surgery, AI applications such as virtual reality (VR) and augmented reality (AR) simulations and intelligent tutoring systems are being utilized to enhance training. This review aims to explore the current applications, benefits, challenges, and future directions of AI in orthopaedic education, while also addressing relevant ethical and logistical considerations. Methods: A targeted literature review was conducted using PubMed, prioritizing studies published in 2024 and including relevant articles from 2023. Search terms included "artificial intelligence", "orthopaedic education", "surgical simulation", and related keywords. Studies were selected based on relevance to orthopaedic surgery education, with a particular focus on surgical skill acquisition, diagnostic training, and curriculum development. Both peer-reviewed and selected non-peer-reviewed sources were analyzed to synthesize current trends and emerging practices. Relevant articles were also identified using manual reference searching. Key Content and Findings: The review highlights a positive shift in attitudes toward AI among educators and learners, particularly for its ability to simulate surgical environments safely and personalize learning. Current applications include AI-powered VR/AR platforms for realistic procedural training, intelligent tutoring systems that tailor feedback to individual learning gaps, and tools for enhancing diagnostic reasoning. Despite these advances, challenges remain, including concerns about overreliance on technology, institutional readiness, and the need for adjustments to the curriculum. Conclusions: AI presents a transformative opportunity for orthopaedic education by enabling safer, more personalized, and more efficient learning. While current applications show promising results in improving both knowledge and technical skill, ongoing evaluation, thoughtful integration, and structured implementation are necessary to maximize educational value while addressing limitations and ethical concerns.
Indexed as
Identifiers
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.