ReviewJournal of medical ultrasonics (2001)2026
Artificial intelligence in ultrasound imaging for carpal tunnel syndrome: what clinicians need to know.
Review in Journal of medical ultrasonics (2001), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review examines artificial intelligence (AI) applications in ultrasound imaging for carpal tunnel syndrome diagnosis. Deep learning models have achieved Dice coefficients exceeding 0.85 for median nerve segmentation and diagnostic accuracy with area under the curve values up to 0.926, often matching specialist performance. However, methodological limitations exist: only three of 13 included studies (23%) performed external validation, and most used single-center retrospective designs. No prospective clinical trials have demonstrated improved patient outcomes. We critically appraise study quality, discuss current limitations, and provide practical recommendations for clinicians considering AI integration into their practice.
Indexed as
Identifiers
42599636What 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.