Using machine learning to predict the rupture risk of multiple intracranial aneurysms
Multiple intracranial aneurysms have distinct mechanisms of formation, progression, and rupture. The widely used PHASES score does not incorporate morphological parameters of aneurysms and is not specifically designed for patients with multiple aneurysms. Therefore, we constructed a risk prediction model for the rupture of MIAs by machine learning algorithms.
Authors
- Junqiang Feng (ORCID: https://orcid.org/0000-0003-0731-6510)
- Liu He (ORCID: https://orcid.org/0000-0002-1349-5343)
- Yu Wang (ORCID: https://orcid.org/0000-0001-7962-4331)
- Chunyi Wang (ORCID: https://orcid.org/0000-0002-7187-5029)
Institutions
- Capital Medical University (CN)
- Chinese Institute for Brain Research (CN)
Publication Details
- Journal
- Frontiers in Neurology
- Published
- 2025-08-04
- DOI
- https://doi.org/10.3389/fneur.2025.1539341
- Primary Topic
- Intracranial Aneurysms: Treatment and Complications
- Type
- article
- Field-Weighted Citation Impact
- 0.00