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Development and Validation of a Model to Identify Critical Brain Injuries Using Natural Language Processing of Text Computed Tomography Reports
22
Zitationen
21
Autoren
2022
Jahr
Abstract
These findings suggest that the BrainNERD model accurately extracted acute brain injury terms and their properties from head CT text reports. This freely available new tool could advance clinical research by integrating information in easily gathered head CT reports to expand knowledge of acute brain injury radiographic phenotypes.
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Autoren
- Victor Torres‐Lopez
- Grace E. Rovenolt
- Angelo J. Olcese
- Gabriella Garcia
- Sarah M. Chacko
- Amber Robinson
- Edward Gaiser
- Julián Acosta
- Alison L. Herman
- Lindsey Kuohn
- Megan Leary
- Alexandria L. Soto
- Qiang Zhang
- Safoora Fatima
- Guido J. Falcone
- Seyedmehdi Payabvash
- Richa Sharma
- Aaron F. Struck
- Kevin N. Sheth
- M. Brandon Westover
- Jennifer A. Kim