SynthesisBMC medical education2025
Artificial intelligence in orthopaedic education, training and research: a systematic review.
Synthesis in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Concerns of Using Large Language Models in Health Care Research and Practice: Umbrella Review.Journal of medical Internet research · 2026Pooled it
- Artificial Intelligence in Orthopaedics: Current Evidence and Clinical Translation Across the Patient Care Pathway.Journal of clinical medicine · 2026Review
- Review
- The global contributions and emerging trends of extended reality-driven transformation in orthopedic surgical education: a bibliometric study.Journal of robotic surgery · 2026Review
- ChatGPT delivers mostly satisfactory but occasionally inaccurate and potentially unsafe answers to hip arthroscopy questions during the surgeon's learning curve.Journal of experimental orthopaedics · 2026Article
- Review
- Transforming thyroid disease education: AI and virtual technologies in residency training.Frontiers in endocrinology · 2026Review
- 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
backgroundArtificial intelligence (AI) increasingly transforms orthopedic education and research, offering novel surgical training and scientific advancement approaches. However, these AI applications' scope, impact, and limitations require comprehensive evaluation. Aim to systematically review AI technologies' practical applications, benefits, limitations, and future directions in orthopedic education and research.
methodsThis systematic review was registered with PROSPERO (CRD420251064596). A comprehensive search of PubMed, Embase, and Scopus was conducted. Studies reporting AI technologies-such as machine learning, virtual reality (VR) simulation, generative AI, and adaptive learning systems-were included in orthopedic training or research. Due to heterogeneity in study designs and outcome measures, data were extracted and synthesized narratively.
resultsAI technologies consistently improve training efficiency, personalized learning, and objective skill assessments. VR simulation and machine learning-based feedback tools enhanced technical proficiency and significantly reduced learning curves. Adaptive learning platforms enabled tailored educational pathways. However, generative AI applications remain nascent, with notable concerns regarding content accuracy and bias. Across studies, key limitations included data bias, over-reliance on automated systems, high implementation costs, and a lack of longitudinal and real-world validation. Most studies were limited to simulation-based environments with insufficient evidence on clinical skill transfer. Ethical, curricular, and regulatory considerations remain underdeveloped.
conclusionsAI holds considerable potential to advance orthopedic education and research by enabling more efficient, equitable, and personalized training. However, its integration must be guided by rigorous validation, ethical standards, and stakeholder collaboration. Hybrid human-AI training models and standardized evaluation metrics are essential to realizing AI's full potential in orthopedics.
Indexed as
Identifiers
What Socratic 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 Socratic graph.