Development and Validation of an Interpretable Machine Learning Model for Predicting Early Fusion After Anterior Cervical Discectomy and Fusion
This exploratory study established an ML-based approach for predicting EF after ACDF, with the SGB algorithm showing relatively strong predictive performance. The identified influential factors may provide preliminary insights for individualized clinical assessment and perioperative management, warranting further validation in multicenter settings.
Authors
- Chen Ding (ORCID: https://orcid.org/0000-0002-9001-8575)
- Tingkui Wu (ORCID: https://orcid.org/0000-0002-4884-0725)
- Shuang Liang (ORCID: https://orcid.org/0000-0002-6289-0972)
- Hao Liu (ORCID: https://orcid.org/0000-0002-2992-6232)
- Kangkang Huang
- Hong Wang (ORCID: https://orcid.org/0000-0002-0253-8918)
- Beiyu Wang
Institutions
- Center for Science in the Public Interest (United States) (US)
- Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
- Datang Telecom Group (China) (CN)
Publication Details
- Journal
- Spine
- Published
- 2025-12-11
- DOI
- https://doi.org/10.1097/brs.0000000000005595
- Primary Topic
- Cervical and Thoracic Myelopathy
- Type
- article
- Field-Weighted Citation Impact
- 0.00