Predictive models for assessing the risk of brain aneurysm rupture
The triage process for aneurysms is highly personalized and can benefit from incorporating clinical data, detailed morphological metrics of the aneurysm, and sophisticated analyses of aneurysm wall enhancement such as radiomics.
Authors
- David Hasan (ORCID: https://orcid.org/0000-0002-8335-5442)
- Santiago Ortega‐Gutiérrez (ORCID: https://orcid.org/0000-0002-3408-1297)
- Linder Hagstrom Wendt (ORCID: https://orcid.org/0000-0003-1832-0486)
- Diego Ojeda (ORCID: https://orcid.org/0000-0001-6528-6087)
- Edgar Andres Samaniego (ORCID: https://orcid.org/0000-0003-2764-2268)
- Mario Zanaty (ORCID: https://orcid.org/0000-0002-6605-690X)
- Samantha Sáenz (ORCID: https://orcid.org/0000-0003-1290-5248)
- Emily Garces
- Andres Gudino (ORCID: https://orcid.org/0009-0003-0123-6138)
- Elena Sagues (ORCID: https://orcid.org/0000-0002-8192-1906)
- Carlos Dier (ORCID: https://orcid.org/0009-0009-8243-9087)
- Connor Aamot
- Navami Shenoy (ORCID: https://orcid.org/0009-0006-4719-4991)
- Isabel Salinas
Institutions
- University of Iowa (US)
- University of Connecticut (US)
- Duke University (US)
- Universidad San Francisco de Quito (EC)
Publication Details
- Journal
- Journal of neurosurgery
- Published
- 2025-05-02
- DOI
- https://doi.org/10.3171/2025.1.jns241772
- Citations
- 3
- Primary Topic
- Intracranial Aneurysms: Treatment and Complications
- Type
- article
- Field-Weighted Citation Impact
- 4.17