Scalable Extraction of Seizure Frequency Information from Clinical Notes Using the Truveta Language Model (P10-9.001)
Extract seizure frequency information at scale from clinical notes in order to examine longitudinal outcomes of patients with epilepsy being treated with cenobamate.
Authors
- Sadra Naddaf-Sh (ORCID: https://orcid.org/0000-0003-1879-901X)
- Louis Ferrari (ORCID: https://orcid.org/0000-0002-7060-6142)
- Mahdi Salehi (ORCID: https://orcid.org/0000-0003-3193-6541)
- Sean Stern (ORCID: https://orcid.org/0009-0002-5266-8371)
- Esther Hehsun Kim (ORCID: https://orcid.org/0000-0002-9576-4411)
- Stuart J. Gilson (ORCID: https://orcid.org/0000-0001-6370-7191)
- Clarence Wade
- Sally Omidvar
- Sumati Ramsinghani
- Saman Zarandioon
- Megan Lipps-Choi
Institutions
- SK Life Science (United States) (US)
Publication Details
- Journal
- Neurology
- Published
- 2025-04-07
- DOI
- https://doi.org/10.1212/wnl.0000000000208549
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00