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

doi:10.1145/3588314

CORC > 自动化研究所 > 中国科学院自动化研究所 > 多模态人工智能系统全国重点实验室

	Combination of Loss-based Active Learning and Semi-supervised Learning for Recognizing Entities in Chinese Electronic Medical Records
	Yan, Jinghui 2; Zong, Chengqing 1,3; Xu, Jinan 2
刊名	ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING
	2023-05-01
卷号	22 期号:5 页码:19
关键词	Electronic medical record loss-based active learning dynamic balance strategy semi-supervised learning
ISSN号	2375-4699
DOI	10.1145/3588314
通讯作者	Yan, Jinghui(jh_yan@bjtu.edu.cn)
英文摘要	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.
WOS关键词	RECOGNITION
WOS研究方向	Computer Science
语种	英语
出版者	ASSOC COMPUTING MACHINERY
WOS记录号	WOS:001005812800001
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/53579]
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.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100049, Peoples R China 2.Beijing Jiaotong Univ, Sch Comp Sci & Informat Technol, Beijing 100044, Peoples R China 3.Beijing Jiaotong Univ, Sch Comp Sci & Informat Technol, 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.