ReviewJSES reviews, reports, and techniques2023
Current clinical applications of artificial intelligence in shoulder surgery: what the busy shoulder surgeon needs to know and what's coming next.
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 9 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
9 citing papers in PubMed, 10 citations in OpenAlex.
- 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.JSES international · 2026Article
- Artificial intelligence in shoulder arthroplasty: latest concepts and clinical integration.Journal of orthopaedic surgery and research · 2026Review
- Artificial intelligence in shoulder and elbow surgery: a bibliometric analysis of affiliation-based collaboration patterns.JSES international · 2026Review
- Digital Health and Smart Technologies in Shoulder Arthroplasty: Emerging Tools and Clinical Implications.Orthopedic research and reviews · 2026Review
- A deep learning algorithm to detect proximal humerus fractures on radiographs.JSES reviews, reports, and techniques · 2025Article
- Evolution of Anchor Polymer Systems Used in Arthroscopic Shoulder Surgery-A Comprehensive Review.Bioengineering (Basel, Switzerland) · 2025Review
- Artificial intelligence to automatically measure on radiographs the postoperative positions of the glenosphere and pivot point after reverse total shoulder arthroplasty.JSES international · 2025Article
- Navigating the future: A comprehensive review of technology in shoulder arthroplasty.Journal of hand and microsurgery · 2025Review
- An accelerated deep learning model can accurately identify clinically important humeral and scapular landmarks on plain radiographs obtained before and after anatomic arthroplasty.International orthopaedics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) is a continuously expanding field with the potential to transform a variety of industries-including health care-by providing automation, efficiency, precision, accuracy, and decision-making support for simple and complex tasks. Basic knowledge of the key features as well as limitations of AI is paramount to understand current developments in this field and to successfully apply them to shoulder surgery. The purpose of the present review is to provide an overview of AI within orthopedics and shoulder surgery exploring current and forthcoming AI applications. Methods: PubMed and Scopus databases were searched to provide a narrative review of the most relevant literature on AI applications in shoulder surgery. Results: Despite the enormous clinical and research potential of AI, orthopedic surgery has been a relatively late adopter of AI technologies. Image evaluation, surgical planning, aiding decision-making, and facilitating patient evaluations over time are some of the current areas of development with enormous opportunities to improve surgical practice, research, and education. Furthermore, the advancement of AI-driven strategies has the potential to create a more efficient medical system that may reduce the overall cost of delivering and implementing quality health care for patients with shoulder pathology. Conclusion: AI is an expanding field with the potential for broad clinical and research applications in orthopedic surgery. Many challenges still need to be addressed to fully leverage the potential of AI to clinical practice and research such as privacy issues, data ownership, and external validation of the proposed models.
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.