Machine learning integration of multi-modal radiomics and clinical factors predicts refracture risk after percutaneous kyphoplasty in postmenopausal women
Abstract This study explores the use of radiomic features extracted from preoperative T2-weighted MRI and CT images, combined with machine learning models, to predict the risk of vertebral refracture after percutaneous kyphoplasty (PKP) in postmenopausal women. We retrospectively collect data from 1...
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| Główni autorzy: | , , , , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
Nature Portfolio
2025-10-01
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| Seria: | Scientific Reports |
| Hasła przedmiotowe: | |
| Dostęp online: | https://doi.org/10.1038/s41598-025-21894-7 |
| Etykiety: |
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