ArticleJournal of imaging2025
Evaluation of AI Performance in Spinal Radiographic Measurements Compared to Radiologists: A Study of Accuracy and Efficiency.
Article in Journal of imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Diagnostic accuracy of artificial intelligence for spinopelvic parameters in standing total spine X-ray and limitations after fusion surgery.Skeletal radiology · 2026Article
- Comment on "Artificial intelligence automated measurements of spinopelvic parameters in adult spinal deformity a systematic review".Spine deformity · 2026Article
- Deep learning-based estimation of sagittal spinal alignment from coronal radiographs.Frontiers in bioengineering and biotechnology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aimed to evaluate the reliability of an AI-based software tool in measuring spinal parameters-Cobb angle, thoracic kyphosis, lumbar lordosis, and pelvic obliquity-compared to manual measurements by radiologists and to assess potential time savings. In this retrospective monocentric study, 56 patients who underwent full-spine weight-bearing X-rays were analyzed. Measurements were independently performed by an experienced radiologist, a radiology resident, and the AI software. A consensus between two senior experts established the ground truth. Lin's Concordance Correlation Coefficient (CCC), mean absolute error (MAE), ICC, and paired
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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.