Developing predictive models for residual back pain after percutaneous vertebral augmentation treatment for osteoporotic thoracolumbar compression fractures based on machine learning technique
Overall, the study demonstrated that machine learning classifiers such as SVM can effectively predict residual back pain for patients with OVCF following PVP while identifying associated predictors in a multivariate manner.
Authors
- Hao Wu (ORCID: https://orcid.org/0000-0002-8118-9989)
- Jiajun Song
- Chao Li (ORCID: https://orcid.org/0000-0002-0734-0011)
- Jiaming Zhou (ORCID: https://orcid.org/0000-0002-0043-3645)
Institutions
- Tianjin Medical University General Hospital (CN)
- Hubei University of Arts and Science (CN)
- Xiangyang Central Hospital (CN)
- Tianjin Medical University (CN)
Publication Details
- Journal
- Journal of Orthopaedic Surgery and Research
- Published
- 2024-11-28
- DOI
- https://doi.org/10.1186/s13018-024-05271-0
- Citations
- 16
- Primary Topic
- Spinal Fractures and Fixation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 9.16