MRI-based deep learning radiomics model for automated classi…
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- DOI 10.1038/s41598-026-56056-w
- PMID https://pubmed.ncbi.nlm.nih.gov/42218311
- PMCID https://www.ncbi.nlm.nih.gov/pmc/articles/13454629
- OpenAlex ID W7162847729
- Type Article
- Language EN
- Published 30 May 2026
- Volume 16 (1)
- Source Scientific Reports
- Publisher Nature Portfolio
- FWCI 9.30
- Countries 2
- Institutions 4
- Added 31 May 2026
- Updated 31 Oct 2026
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MRI-based deep learning radiomics model for automated classification of disc degeneration in the lumbar spine
Article 2026 EN Gold
Disc degeneration in the lumbar spine is a major cause of low back pain (LBP). The accurate grading of disc degeneration on magnetic resonance imaging (MRI) is critical for clinical management and patient selection for spine surgery. This study aims to develop and evaluate machine learning (ML) models that combine features from deep learning (DL) and radiomics for the automated prediction of Pfirr…
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5 authors| # | Author | Institutions | ORCID |
|---|---|---|---|
| 1 | Shiv Patil | Thomas Jefferson University (US) | |
| 2 | Om H. Gandhi | Hospital of the University of … (US) University of Oxford (GB) | |
| 3 | Mert Karabacak | Mount Sinai Health System (US) | |
| 4 | Matthew T. Carr | Mount Sinai Health System (US) | |
| 5 | Konstantinos D. Margetis Corresponding | Mount Sinai Health System (US) |
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