Long‐term epilepsy outcome dynamics revealed by natural language processing of clinic notes
Abstract
Electronic medical records allow for retrospective clinical research with large patient cohorts. However, epilepsy outcomes are often contained in free text notes that are difficult to mine. We recently developed and validated novel natural language processing (NLP) algorithms to automatically extract key epilepsy outcome measures from clinic notes. In this study, we assessed the feasibility of extracting these measures to study the natural history of epilepsy at our center.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- May 10, 2023
- Source ID
- 10.1111/epi.17633
Entities
People
- Brian Litt
- Chloé E. Hill
- Colin A Ellis
- Dan Roth
- Erin C. Conrad
- Kathryn A Davis
- Kevin Xie
- Russell T Shinohara
- Ryan S. Gallagher
- Sharon X. Xie
Organizations
- American Academy of Neurology
- National Institute of Neurological Disorders and Stroke
- Office of Naval Research
- University of Michigan
- University of Pennsylvania