Application and performance of deep learning models for the automated diagnosis of cervical central spinal stenosis on MRI: a systematic review
Deep-learning shows promising diagnostic performance for automated CCSS assessment on MRI and could reduce variability and reporting time. However, generalisability remains uncertain due to small, retrospective, largely single-centre cohorts and scarce external validation. Standardized reporting (e.g., CLAIM) and prospective, multi-centre validation is needed before routine clinical deployment.
Institutions
- German Cancer Research Center (DE)
- Heidelberg University (DE)
- University Hospital Heidelberg (DE)
Publication Details
- Journal
- Brain and Spine
- Published
- 2025-12-19
- DOI
- https://doi.org/10.1016/j.bas.2025.105902
- Primary Topic
- Cervical and Thoracic Myelopathy
- Type
- article
- Field-Weighted Citation Impact
- 0.00