An Open Natural Language Processing Development Framework for EHR-based Clinical Research: A case demonstration using the National COVID Cohort Collaborative (N3C)
Abstrak
While we pay attention to the latest advances in clinical natural language processing (NLP), we can notice some resistance in the clinical and translational research community to adopt NLP models due to limited transparency, interpretability, and usability. In this study, we proposed an open natural language processing development framework. We evaluated it through the implementation of NLP algorithms for the National COVID Cohort Collaborative (N3C). Based on the interests in information extraction from COVID-19 related clinical notes, our work includes 1) an open data annotation process using COVID-19 signs and symptoms as the use case, 2) a community-driven ruleset composing platform, and 3) a synthetic text data generation workflow to generate texts for information extraction tasks without involving human subjects. The corpora were derived from texts from three different institutions (Mayo Clinic, University of Kentucky, University of Minnesota). The gold standard annotations were tested with a single institution's (Mayo) ruleset. This resulted in performances of 0.876, 0.706, and 0.694 in F-scores for Mayo, Minnesota, and Kentucky test datasets, respectively. The study as a consortium effort of the N3C NLP subgroup demonstrates the feasibility of creating a federated NLP algorithm development and benchmarking platform to enhance multi-institution clinical NLP study and adoption. Although we use COVID-19 as a use case in this effort, our framework is general enough to be applied to other domains of interest in clinical NLP.
Penulis (32)
Sijia Liu
Andrew Wen
Liwei Wang
Huan He
Sunyang Fu
Robert Miller
Andrew Williams
Daniel Harris
Ramakanth Kavuluru
Mei Liu
Noor Abu-el-rub
Dalton Schutte
Rui Zhang
Masoud Rouhizadeh
John D. Osborne
Yongqun He
Umit Topaloglu
Stephanie S Hong
Joel H Saltz
Thomas Schaffter
Emily Pfaff
Christopher G. Chute
Tim Duong
Melissa A. Haendel
Rafael Fuentes
Peter Szolovits
Hua Xu
Hongfang Liu
National COVID Cohort Collaborative
Natural Language Processing
Subgroup
National COVID Cohort Collaborative
Akses Cepat
- Tahun Terbit
- 2021
- Bahasa
- en
- Sumber Database
- arXiv
- Akses
- Open Access ✓