ReviewDiagnostic and interventional radiology (Ankara, Turkey)2025
Artificial intelligence in musculoskeletal applications: a primer for radiologists.
Review in Diagnostic and interventional radiology (Ankara, Turkey), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- A Hybrid Automatic Model for Circle Detection in X-Ray Imagery: A Case Study on Hip Prosthesis Wear.Bioengineering (Basel, Switzerland) · 2026Article
- Artificial Intelligence in Lung Cancer: A Narrative Review of Recent Advances in Diagnosis, Biomarker Discovery, and Drug Development.Pharmaceutics · 2026Review
- Bone-CNN: A Lightweight Deep Learning Architecture for Multi-Class Classification of Primary Bone Tumours in Radiographs.Biomedicines · 2026Article
- Optimizing the power of AI for fracture detection: from blind spots to breakthroughs.Skeletal radiology · 2025Review
- AI for Lesion Detection in Musculoskeletal Radiology.Journal of the Korean Society of Radiology · 2025Review
- Deep learning-driven abbreviated knee MRI protocols: diagnostic accuracy in clinical practice.La Radiologia medica · 2025Article
- Artificial intelligence-assisted analysis of musculoskeletal imaging-A narrative review of the current state of machine learning models.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025Review
- Advancements in Machine Learning for Precision Diagnostics and Surgical Interventions in Interconnected Musculoskeletal and Visual Systems.Journal of clinical medicine · 2025Review
- Review
- Recent topics in musculoskeletal imaging focused on clinical applications of AI: How should radiologists approach and use AI?La Radiologia medica · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As an umbrella term, artificial intelligence (AI) covers machine learning and deep learning. This review aimed to elaborate on these terms to act as a primer for radiologists to learn more about the algorithms commonly used in musculoskeletal radiology. It also aimed to familiarize them with the common practices and issues in the use of AI in this domain.
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.