A Dynamic Machine Learning Model to Predict Angiographic Vasospasm After Aneurysmal Subarachnoid Hemorrhage
Longitudinal TCD data can be used to create a dynamic machine learning model with higher precision than static TCD measurements for predicting AV after aSAH.
Authors
- Margaret Louise McGrath (ORCID: https://orcid.org/0000-0002-6384-5540)
- Michael R. Levitt (ORCID: https://orcid.org/0000-0003-3612-3347)
- Christine T. Fong (ORCID: https://orcid.org/0000-0001-5090-273X)
- Rajeev Sen (ORCID: https://orcid.org/0000-0002-9105-1668)
- Abhijit V. Lele (ORCID: https://orcid.org/0000-0002-6956-538X)
- Louis J. Kim
- Christine Park (ORCID: https://orcid.org/0000-0002-0066-366X)
- Lucy Lu Wang (ORCID: https://orcid.org/0009-0003-1917-6014)
- Varadaraya S. Shenoy
- R. Michael Meyer
- Laligam N. Sekhar
Institutions
- University of Washington (US)
- Harborview Medical Center (US)
- NYU Langone Health (US)
- Neurological Surgery (US)
Publication Details
- Journal
- Neurosurgery
- Published
- 2025-07-24
- DOI
- https://doi.org/10.1227/neu.0000000000003639
- Citations
- 2
- Primary Topic
- Intracranial Aneurysms: Treatment and Complications
- Type
- article
- Field-Weighted Citation Impact
- 2.78