MedJEx: A Medical Jargon Extraction Model with Wiki’s Hyperlink Span and Contextualized Masked Language Model Score

Sunjae Kwon, Zonghai Yao, Harmon Jordan, David Levy, Brian Corner, Hong Yu


Abstract
This paper proposes a new natural language processing (NLP) application for identifying medical jargon terms potentially difficult for patients to comprehend from electronic health record (EHR) notes. We first present a novel and publicly available dataset with expert-annotated medical jargon terms from 18K+ EHR note sentences (MedJ). Then, we introduce a novel medical jargon extraction (MedJEx) model which has been shown to outperform existing state-of-the-art NLP models. First, MedJEx improved the overall performance when it was trained on an auxiliary Wikipedia hyperlink span dataset, where hyperlink spans provide additional Wikipedia articles to explain the spans (or terms), and then fine-tuned on the annotated MedJ data. Secondly, we found that a contextualized masked language model score was beneficial for detecting domain-specific unfamiliar jargon terms. Moreover, our results show that training on the auxiliary Wikipedia hyperlink span datasets improved six out of eight biomedical named entity recognition benchmark datasets. MedJEx is publicly available.
Anthology ID:
2022.emnlp-main.805
Volume:
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates
Editors:
Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
11733–11751
Language:
URL:
https://aclanthology.org/2022.emnlp-main.805
DOI:
10.18653/v1/2022.emnlp-main.805
Bibkey:
Cite (ACL):
Sunjae Kwon, Zonghai Yao, Harmon Jordan, David Levy, Brian Corner, and Hong Yu. 2022. MedJEx: A Medical Jargon Extraction Model with Wiki’s Hyperlink Span and Contextualized Masked Language Model Score. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 11733–11751, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
Cite (Informal):
MedJEx: A Medical Jargon Extraction Model with Wiki’s Hyperlink Span and Contextualized Masked Language Model Score (Kwon et al., EMNLP 2022)
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PDF:
https://preview.aclanthology.org/ingest-2024-clasp/2022.emnlp-main.805.pdf