ArticleProceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing2022
MedJEx: A Medical Jargon Extraction Model with Wiki's Hyperlink Span and Contextualized Masked Language Model Score.
Article in Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Article
- Chatbot To Help Patients Understand Their Health.Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing · 2025Article
- MedReadCtrl: Personalizing medical text generation with readability-controlled instruction learning.medRxiv : the preprint server for health sciences · 2025Article
- MedReadMe: A Systematic Study for Fine-grained Sentence Readability in Medical Domain.Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing · 2024Article
- README: Bridging Medical Jargon and Lay Understanding for Patient Education through Data-Centric NLP.Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing · 2024Article
- NoteChat: A Dataset of Synthetic Patient-Physician Conversations Conditioned on Clinical Notes.Findings of ACL. ACL · 2024Article
- ODD: A Benchmark Dataset for the Natural Language Processing Based Opioid Related Aberrant Behavior Detection.Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting · 2024Article
- Automated identification of eviction status from electronic health record notes.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Context Variance Evaluation of Pretrained Language Models for Prompt-based Biomedical Knowledge Probing.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
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 (
Identifiers
37103473PMC10129059What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.