ArticleScientific reports2025
An end-to-end pipeline for automated scoliosis diagnosis with standardized clinical reporting using SNOMED CT.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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
1 citing paper in PubMed.
- Intelligence Architectures and Machine Learning Applications in Contemporary Spine Care.Bioengineering (Basel, Switzerland) · 2025Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent advancements in automated scoliosis diagnosis using X-ray imaging have focused on detecting spinal curvature through angle measurements, but they often lack systematically standardized clinical terminology schemes. To address these limitations, we propose an end-to-end pipeline that detects individual vertebrae and Cobb angles including reports of structured medical terms. The performance of the proposed pipeline was evaluated on the SpineWeb public dataset, achieving state-of-the-art results with a Circular Mean Absolute Error of 3.50 and Symmetric Mean Absolute Percentage Error of 7.35, outperforming existing methods in both accuracy and efficiency. The results are defined and reported using SNOMED CT-based templates to improve data quality and facilitate efficient secondary use. We have designed our solution to perform large-scale data analysis and inter-hospital comparisons, which can positively impact the healthcare of spinal scoliosis patients.
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Registered trials
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