ReviewInternational journal of environmental research and public health2022
Artificial Intelligence in the Management of Rotator Cuff Tears.
Review in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed.
- Biologic augmentation in rotator cuff repair: current evidence and future directions.JSES reviews, reports, and techniques · 2026Review
- Tele-Rehabilitation and Tele-Diagnostics in Shoulder Disorders: Current Evidence, Challenges, and Future Directions-A Narrative Review.Journal of clinical medicine · 2026Review
- Article
- Artificial intelligence in shoulder and elbow surgery: a bibliometric analysis of affiliation-based collaboration patterns.JSES international · 2026Review
- Advances in Shoulder Pain Imaging: A Narrative Review of Current Practice and Emerging Trends.Current medical imaging · 2025Article
- Artificial Intelligence for the Diagnosis and Management of Patellofemoral Instability: A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2025Review
- Trustworthy deep learning for the automated quantification of the fatty infiltration of the rotator cuff muscles using magnetic resonance imaging.JSES international · 2025Article
- Augmentation Techniques for Rotator Cuff Repairs.JBJS reviews · 2025Review
- Deep Learning Models to Detect Anterior Cruciate Ligament Injury on MRI: A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2025Review
- Detection of Acromion Types in Shoulder Magnetic Resonance Image Examination with Developed Convolutional Neural Network and Textural-Based Content-Based Image Retrieval System.Journal of clinical medicine · 2025Article
- Exploring artificial intelligence in orthopaedics: A collaborative survey from the ISAKOS Young Professional Task Force.Journal of experimental orthopaedics · 2025Article
- The Rise of Artificial Intelligence in Orthopedics: A Bibliometric and Visualization Analysis.Journal of multidisciplinary healthcare · 2025Article
- Revision Surgery for Shoulder Infection after Arthroscopic Rotator Cuff Repair: Functional Outcomes and Eradication Rate-A Systematic Review.Healthcare (Basel, Switzerland) · 2024Review
- Application of Artificial Intelligence in Shoulder Pathology.Diagnostics (Basel, Switzerland) · 2024Review
- Arthroscopic rotator cuff repair in patients over 65 years of age: successful functional outcomes and a high tendon integrity rate can be obtained after surgery.JSES international · 2024Article
- Advancements in the diagnosis and management of rotator cuff tears. The role of artificial intelligence.Journal of orthopaedics · 2024Review
- Deep-Learning-Based Automated Rotator Cuff Tear Screening in Three Planes of Shoulder MRI.Diagnostics (Basel, Switzerland) · 2023Article
- Approaching Artificial Intelligence in Orthopaedics: Predictive Analytics and Machine Learning to Prognosticate Arthroscopic Rotator Cuff Surgical Outcomes.Journal of clinical medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Technological innovation is a key component of orthopedic surgery. Artificial intelligence (AI), which describes the ability of computers to process massive data and "learn" from it to produce outputs that mirror human cognition and problem solving, may become an important tool for orthopedic surgeons in the future. AI may be able to improve decision making, both clinically and surgically, via integrating additional data-driven problem solving into practice. The aim of this article will be to review the current applications of AI in the management of rotator cuff tears. The article will discuss various stages of the clinical course: predictive models and prognosis, diagnosis, intraoperative applications, and postoperative care and rehabilitation. Throughout the article, which is a review in terms of study design, we will introduce the concept of AI in rotator cuff tears and provide examples of how these tools can impact clinical practice and patient care. Though many advancements in AI have been made regarding evaluating rotator cuff tears-particularly in the realm of diagnostic imaging-further advancements are required before they become a regular facet of daily clinical practice.
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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.