Prediction of Response to Spinal Cord Stimulation Using Machine Learning Based on Radiomics and Patient-Reported Outcomes
Our study demonstrates the value of ML models combined with systematic feature selection in predicting clinical outcomes, emphasizing the importance of integrating radiomics and clinical variables for improved model interpretability and robustness.
Authors
- Ilknur Telkes (ORCID: https://orcid.org/0000-0003-1421-5910)
- Julie G. Pilitsis (ORCID: https://orcid.org/0000-0002-6488-9692)
- Tessa Harland (ORCID: https://orcid.org/0009-0003-0961-3989)
- Eung‐Joo Lee (ORCID: https://orcid.org/0000-0001-6386-8470)
- Barbara Buccilli (ORCID: https://orcid.org/0000-0002-3084-0217)
- Meghan L. Edgerton
Institutions
- University of Arizona (US)
- Albany Medical Center Hospital (US)
- Icahn School of Medicine at Mount Sinai (US)
Publication Details
- Journal
- Neurosurgery
- Published
- 2025-08-29
- DOI
- https://doi.org/10.1227/neu.0000000000003715
- Citations
- 2
- Primary Topic
- Pain Management and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 4.38