A Multi-event Extraction Model for Nursing Records

Ruoyu Song, Lan Wei, Yuhang Guo*

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Nursing records contain information on patients’ treatment processes, which reflect the changes in patients’ conditions and have legal effects. However, some of the written records of intensive care unit (ICU) nurses are incomplete according to our observations. This paper proposes an approach extracting structured nursing events from unstructured nursing records for detecting the missing items automatically. According to the PIO (problem, intervention, outcome) principle in the field of medical care, we propose event schemas for nursing records and annotate a Chinese nursing event extraction dataset (CNEED) on ICU nursing records. We find that several events may occur in a nursing record. Therefore, we present a multi-event extraction model for the nursing records. The experimental results demonstrate that our model achieves good results on CNEED and outperforms competitive methods on the multi-event argument attribution problem. By observing the results of automatic event extraction by our model, we detect missing items in the existing nursing records. This proves that our model can be used to help nurses check and improve the method of recording nursing processes.

源语言英语
主期刊名Data Science - 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022, Proceedings
编辑Yang Wang, Liehui Zhang, Guobin Zhu, Qilong Han, Xianhua Song, Zeguang Lu
出版商Springer Science and Business Media Deutschland GmbH
146-158
页数13
ISBN(印刷版)9789811952081
DOI
出版状态已出版 - 2022
活动8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022 - Chengdu, 中国
期限: 19 8月 202222 8月 2022

出版系列

姓名Communications in Computer and Information Science
1629 CCIS
ISSN(印刷版)1865-0929
ISSN(电子版)1865-0937

会议

会议8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022
国家/地区中国
Chengdu
时期19/08/2222/08/22

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