ReviewJSES reviews, reports, and techniques2023
Artificial intelligence-based applications in shoulder surgery leaves much to be desired: a systematic review.
Review in JSES reviews, reports, and techniques, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 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
26 citing papers in PubMed.
- Machine learning-based prediction of retear after arthroscopic rotator cuff repair: a multicenter cohort study.JSES international · 2026Article
- Role of artificial intelligence in head and neck surgery - A narrative review.Turkish journal of surgery · 2026Article
- Artificial Intelligence in Arthroplasty: A Comprehensive Structured Critical Review and Descriptive Evidence Map of Validation, Uncertainty, and Workflow Integration.Bioengineering (Basel, Switzerland) · 2026Review
- Artificial Intelligence in Orthopaedics: Current Evidence and Clinical Translation Across the Patient Care Pathway.Journal of clinical medicine · 2026Review
- Artificial intelligence in shoulder arthroplasty: latest concepts and clinical integration.Journal of orthopaedic surgery and research · 2026Review
- Quantifying the Contribution of Bone Morphology to Implant Selection in Shoulder Arthroplasty Using CT-Based Deep Learning.Bioengineering (Basel, Switzerland) · 2026Article
- Artificial Intelligence and its Current Role in Clinical Outcome Prediction, Musculoskeletal Imaging, and Economic and Ethical Considerations within Orthopedics and Sports Medicine.Current reviews in musculoskeletal medicine · 2026Review
- Tele-Rehabilitation and Tele-Diagnostics in Shoulder Disorders: Current Evidence, Challenges, and Future Directions-A Narrative Review.Journal of clinical medicine · 2026Review
- Artificial intelligence in surgical decision-making across the perioperative continuum: a scoping review.Frontiers in digital health · 2026Review
- Artificial intelligence in shoulder and elbow surgery: a bibliometric analysis of affiliation-based collaboration patterns.JSES international · 2026Review
- Review
- Advances in Shoulder Pain Imaging: A Narrative Review of Current Practice and Emerging Trends.Current medical imaging · 2025Article
- Assessing the accuracy of a machine learning prediction for 2 different shoulder prostheses: an external validation study.JSES international · 2025Article
- An overview of artificial intelligence and machine learning in shoulder surgery.Clinics in shoulder and elbow · 2025Article
- Artificial intelligence for predicting 30-day mortality after surgery for femoral shaft fractures: A retrospective study.Indian journal of anaesthesia · 2025Article
- Navigating the future: A comprehensive review of technology in shoulder arthroplasty.Journal of hand and microsurgery · 2025Review
- Robotics in arthroplasty: how good are they?JSES international · 2025Review
- Ethical considerations in shoulder arthroplasty in patients who are obese.JSES reviews, reports, and techniques · 2025Review
- Can Artificial Intelligence Reliably and Accurately Measure Lower Limb Alignment: A Systematic Review and Meta-Analysis.The archives of bone and joint surgery · 2025Review
- Artificial Intelligence in Surgery: A Systematic Review of Use and Validation.Journal of clinical 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) aims to simulate human intelligence using automated computer algorithms. There has been a rapid increase in research applying AI to various subspecialties of orthopedic surgery, including shoulder surgery. The purpose of this review is to assess the scope and validity of current clinical AI applications in shoulder surgery literature. Methods: A systematic literature review was conducted using PubMed for all articles published between January 1, 2010 and June 10, 2022. The search query used the terms as follows: Results: A total of 45 studies were included in the final analysis. Eighteen studies involved shoulder arthroplasty, 13 rotator cuff, and 14 other areas. Studies applying AI to shoulder surgery primarily involved (1) automated imaging analysis including identifying rotator cuff tears and shoulder implants (2) risk prediction analyses including perioperative complications, functional outcomes, and patient satisfaction. Highest model performance area under the curve ranged from 0.681 (poor) to 1.00 (perfect). Only 2 studies reported external validation. Conclusion: Applications of AI in the field of shoulder surgery are expanding rapidly and offer patient-specific risk stratification for shared decision-making and process automation for resource preservation. However, model performance is modest and external validation remains to be demonstrated, suggesting increased scientific rigor is warranted prior to deploying AI-based clinical applications.
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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.