Machine-learning models for the prediction of ideal surgical outcomes in patients with adult spinal deformity
In this prognostic study, we developed a machine-learning model that accurately predicted outcome after surgery for ASD. The model is built on routinely modifiable indicators, thereby facilitating its integration into clinical practice to promote optimized decision-making.
Authors
- Shuaikang Wang (ORCID: https://orcid.org/0000-0001-5232-2456)
- Dongfan Wang (ORCID: https://orcid.org/0000-0003-2869-3809)
- Peng Cui (ORCID: https://orcid.org/0000-0002-1636-4832)
- Shibao Lu (ORCID: https://orcid.org/0000-0001-7052-7041)
- Xiaolong Chen (ORCID: https://orcid.org/0000-0002-8128-0969)
- Di Han
- Qijun Wang
Institutions
- Capital Medical University (CN)
Publication Details
- Journal
- The Bone & Joint Journal
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1302/0301-620x.107b3.bjj-2024-1220.r1
- Citations
- 6
- Primary Topic
- Scoliosis diagnosis and treatment
- Type
- article
- Field-Weighted Citation Impact
- 12.04