Span-based annotation framework for LLM-based clinical named entity recognition: development and validation using Korean emergency department notes

This study introduced a novel span-based annotation framework for LLM-based clinical NER verified by three independent experiments. In multilingual and real-world clinical settings, LLMs have proven in handling complex entity spans that include word-level and phrase-level annotations, particularly for long and attribute-rich entities.

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Publication Details

Journal
JAMIA Open
Published
2025-11-03
DOI
https://doi.org/10.1093/jamiaopen/ooaf157
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
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article

Span-based annotation framework for LLM-based clinical named entity recognition: development and validation using Korean emergency department notes

Eun Hye Jang, Sangji Lee, Hyungpil Moon, Javier Aguirre et al.
JAMIA Open
Topic Modeling
article

Span-based annotation framework for LLM-based clinical named entity recognition: development and validation using Korean emergency department notes

Eun Hye Jang, Sangji Lee, Hyungpil Moon, Javier Aguirre, Won Chul
article en

Abstract

This study introduced a novel span-based annotation framework for LLM-based clinical NER verified by three independent experiments. In multilingual and real-world clinical settings, LLMs have proven in handling complex entity spans that include word-level and phrase-level annotations, particularly for long and attribute-rich entities.

JAMIA OpenVol. 8(6)
Samsung Medical Center (KR), Sungkyunkwan University (KR)
Openalex Percentile: Top 80%
Topic Modeling
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