ReviewJournal of the Korean Society of Radiology2025
[Current Landscape and Commercialization of AI Models in Musculoskeletal Imaging].
Review in Journal of the Korean Society of Radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
- Erratum issued
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
AI-based software as a medical device (SaMD) using deep learning applications for musculoskeletal diseases is being clinically implemented in South Korea, although it is still in its early stages in the musculoskeletal field compared to other fields of radiology, such as neuroradiology, chest, and breast imaging. AI models for detecting various fractures, estimating pediatric bone age, calculating geometric skeleton measurements, grading arthritis, and osteoporosis screening have shown high diagnostic performance, and many of these applications are now commercially available for use in clinical practice. Many studies have documented the feasibility of using an AI model for detecting joint pathology on MRI and interpreting spine MRIs. This review provides information on the domestic and international commercialization status of AI-based SaMD for musculoskeletal imaging and beneficial considerations for its application in clinical practice, helping readers who are interested in the field application of musculoskeletal imaging AI models in their decision-making.
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.