Not a cute stroke: Analysis of Rule- and Neural Network-based Information Extraction Systems for Brain Radiology Reports

Andreas Grivas, Beatrice Alex, Claire Grover, Richard Tobin, William Whiteley


Abstract
We present an in-depth comparison of three clinical information extraction (IE) systems designed to perform entity recognition and negation detection on brain imaging reports: EdIE-R, a bespoke rule-based system, and two neural network models, EdIE-BiLSTM and EdIE-BERT, both multi-task learning models with a BiLSTM and BERT encoder respectively. We compare our models both on an in-sample and an out-of-sample dataset containing mentions of stroke findings and draw on our error analysis to suggest improvements for effective annotation when building clinical NLP models for a new domain. Our analysis finds that our rule-based system outperforms the neural models on both datasets and seems to generalise to the out-of-sample dataset. On the other hand, the neural models do not generalise negation to the out-of-sample dataset, despite metrics on the in-sample dataset suggesting otherwise.
Anthology ID:
2020.louhi-1.4
Volume:
Proceedings of the 11th International Workshop on Health Text Mining and Information Analysis
Month:
November
Year:
2020
Address:
Online
Editors:
Eben Holderness, Antonio Jimeno Yepes, Alberto Lavelli, Anne-Lyse Minard, James Pustejovsky, Fabio Rinaldi
Venue:
Louhi
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
24–37
Language:
URL:
https://aclanthology.org/2020.louhi-1.4
DOI:
10.18653/v1/2020.louhi-1.4
Bibkey:
Cite (ACL):
Andreas Grivas, Beatrice Alex, Claire Grover, Richard Tobin, and William Whiteley. 2020. Not a cute stroke: Analysis of Rule- and Neural Network-based Information Extraction Systems for Brain Radiology Reports. In Proceedings of the 11th International Workshop on Health Text Mining and Information Analysis, pages 24–37, Online. Association for Computational Linguistics.
Cite (Informal):
Not a cute stroke: Analysis of Rule- and Neural Network-based Information Extraction Systems for Brain Radiology Reports (Grivas et al., Louhi 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-5/2020.louhi-1.4.pdf
Video:
 https://slideslive.com/38940043
Code
 edinburgh-ltg/edieviz
Data
BLUE