ReviewSkeletal radiology2022
Musculoskeletal trauma and artificial intelligence: current trends and projections.
Review in Skeletal radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 30 citations in OpenAlex.
- Towards High-Accuracy Athletic Injury Predictions Using a First-Principles Modelling Approach: Theory to (Future) Practice.Sports medicine (Auckland, N.Z.) · 2026Review
- AI in Musculoskeletal Imaging: An End-to-End Perspective.Journal of clinical medicine · 2026Review
- Artificial intelligence in trauma care: applications, ethical challenges, and pathways toward responsible integration.Current opinion in anaesthesiology · 2026Article
- Artificial Intelligence in Orthopaedics: Clinical Performance, Limitations, and Translational Readiness-A Review.Journal of clinical medicine · 2026Review
- Revolutionizing emergency care: an overview of the transformative role of artificial intelligence in diagnosis, triage, and patient management.International journal of emergency medicine · 2025Review
- Artificial Intelligence in Orthopaedic and Trauma Surgery Education: Applications, Ethics, and Future Perspectives.Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews · 2025Review
- How New Technologies Will Transform Total Knee Arthroplasty from a Singular Surgical Procedure to a Holistic Standardized Process.Journal of clinical medicine · 2025Article
- AI applications in musculoskeletal imaging: a narrative review.European radiology experimental · 2024Review
- Development and evaluation of a deep learning-based model for simultaneous detection and localization of rib and clavicle fractures in trauma patients' chest radiographs.Trauma surgery & acute care open · 2024Article
- Ethical considerations in telehealth and artificial intelligence for work related musculoskeletal disorders: A scoping review.Work (Reading, Mass.) · 2024Article
- Artificial Intelligence in Emergency Radiology: Where Are We Going?Diagnostics (Basel, Switzerland) · 2022Review
- Artificial Intelligence in Orthopedic Radiography Analysis: A Narrative Review.Diagnostics (Basel, Switzerland) · 2022Review
- Musculoskeletal MR Image Segmentation with Artificial Intelligence.Advances in clinical radiology · 2022Article
- The current role of the virtual elements of artificial intelligence in total knee arthroplasty.EFORT open reviews · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Musculoskeletal trauma accounts for a significant fraction of emergency department visits and patients seeking urgent care, with a high financial cost to society. Diagnostic imaging is indispensable in the workup and management of trauma patients. However, diagnostic imaging represents a complex multifaceted system, with many aspects of its workflow prone to inefficiencies or human error. Recent technological innovations in artificial intelligence and machine learning have shown promise to revolutionize our systems for providing medical care to patients. This review will provide a general overview of the current state of artificial intelligence and machine learning applications in different aspects of trauma imaging and provide a vision for how such applications could be leveraged to enhance our diagnostic imaging systems and optimize patient outcomes.
Indexed as
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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.