Combination of Loss-based Active Learning and Semi-supervised Learning for Recognizing Entities in Chinese Electronic Medical Records

doi:10.1145/3588314

	Combination of Loss-based Active Learning and Semi-supervised Learning for Recognizing Entities in Chinese Electronic Medical Records
	Yan, Jinghui 1; Zong, Chengqing2,3 ; Xu, Jinan 1
发表期刊	ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING
ISSN	2375-4699
	2023-05-01
卷号	22 期号:5 页码:19
通讯作者	Yan, Jinghui(jh_yan@bjtu.edu.cn)
摘要	The recognition of entities in an electronic medical record (EMR) is especially important to downstream tasks, such as clinical entity normalization and medical dialogue understanding. However, in the medical professional field, training a high-quality named entity recognition system always requires large-scale annotated datasets, which are highly expensive to obtain. In this article, to lower the cost of data annotation andmaximizing the use of unlabeled data, we propose a hybrid approach to recognizing the entities in Chinese electronic medical record, which is in combination of loss-based active learning and semi-supervised learning. Specifically, we adopted a dynamic balance strategy to dynamically balance the minimum loss predicted by a named entity recognition decoder and a loss prediction module at different stages in the process. Experimental results demonstrated our proposed framework's effectiveness and efficiency, achieving higher performances than existing approaches on Chinese EMR entity recognition datasets under limited labeling resources.
关键词	Electronic medical record loss-based active learning dynamic balance strategy semi-supervised learning
DOI	10.1145/3588314
关键词[WOS]	RECOGNITION
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:001005812800001
出版者	ASSOC COMPUTING MACHINERY
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/53580
专题	多模态人工智能系统全国重点实验室
通讯作者	Yan, Jinghui
作者单位	1.Beijing Jiaotong Univ, Sch Comp Sci & Informat Technol, Beijing 100044, Peoples R China 2.Beijing Jiaotong Univ, Sch Comp Sci & Informat Technol, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Yan, Jinghui,Zong, Chengqing,Xu, Jinan. Combination of Loss-based Active Learning and Semi-supervised Learning for Recognizing Entities in Chinese Electronic Medical Records[J]. ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING,2023,22(5):19.
APA	Yan, Jinghui,Zong, Chengqing,&Xu, Jinan.(2023).Combination of Loss-based Active Learning and Semi-supervised Learning for Recognizing Entities in Chinese Electronic Medical Records.ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING,22(5),19.
MLA	Yan, Jinghui,et al."Combination of Loss-based Active Learning and Semi-supervised Learning for Recognizing Entities in Chinese Electronic Medical Records".ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING 22.5(2023):19.