Automated extraction of post-stroke functional outcomes from unstructured electronic health records
The NLP-based model is suitable for use in large-scale phenotyping of stroke functional outcomes and population health research.
Authors
- Marta Fernandes (ORCID: https://orcid.org/0000-0002-7203-2832)
- Michael Brandon Westover (ORCID: https://orcid.org/0000-0003-4803-312X)
- Sahar F. Zafar (ORCID: https://orcid.org/0000-0001-5252-5376)
- Kaileigh Gallagher (ORCID: https://orcid.org/0009-0005-2802-9790)
- Aneesh B. Singhal (ORCID: https://orcid.org/0000-0002-2641-5277)
- Niels Turley (ORCID: https://orcid.org/0009-0009-4806-578X)
- Aditya Gupta (ORCID: https://orcid.org/0000-0002-5243-368X)
Institutions
- Beth Israel Deaconess Medical Center (US)
- Massachusetts General Hospital (US)
Publication Details
- Journal
- European Stroke Journal
- Published
- 2025-01-22
- DOI
- https://doi.org/10.1177/23969873251314340
- Citations
- 1
- Primary Topic
- Acute Ischemic Stroke Management
- Type
- article
- Field-Weighted Citation Impact
- 1.35
Funders
- National Institutes of Health