This repository has been archived and is no longer maintained. The code is provided for historical reference and may contain unpatched or unknown vulnerabilities. It should not be used in production systems.
This repository contains four synthetic clinical notes created by the authors. All notes have been manually and automatically annotated in four domains of whole-person function.
Notes are provided in plaintext (data/txt) and GATE XML format (data/xml), and screenshots of the notes visualized in the GATE tool are available in screenshots.
This repository is released under the CC-BY 2.0 license.
The following citation should be used for attribution:
Gary Allen, Julia Porcino, Jonathan Camacho Maldonado, Maryanne Sacco, Kathleen Coale, Rafael Jiménez Silva, Bart Desmet, Elizabeth Rasch (2023, March 13). Use of Natural Language Processing to Identify Activity Reports in Synthetic Medical Progress Notes [Poster Abstract]. American Medical Informatics Association (AMIA) 2023 Informatics Summit, Seattle, WA, United States.