A hybrid system for temporal relation extraction from discharge summaries

NCUIR > College of Electrical Engineering & Computer Science > Department of Computer Science and information Engineering > journal & Dissertation > Item 987654321/106036

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/106036

Title:	A hybrid system for temporal relation extraction from discharge summaries
Authors:	蔡宗翰;Yang, Yueh-Lin;Lai, Po-Ting;Tsai, Richard Tzong-Han
Contributors:	資訊電機學院資訊工程學系
Keywords:	Artificial intelligence;conditional random fields;discharge summaries;Information retrieval;Pattern recognition;temporal relation extraction
Date:	2014-01-01
Issue Date:	2026-04-23 13:04:45 (UTC+8)
Publisher:	Springer Verlag;Switzerland: Springer International Publishing AG
Abstract:	摘要： Automatically detecting temporal relations among dates/times and events mentioned in patient records has much potential to help medical staff in understanding disease progression and patients response to treatments. It can also facilitate evidence-based medicine (EBM) research. In this paper, we propose a hybrid temporal relation extraction approach which combines patient-record-specific rules and the Conditional Random Fields (CRFs) model to process patient records. We evaluate our approach on i2b2 dataset, and the results show our approach achieves an F-score of 61%. 出版者： Switzerland: Springer International Publishing AG 出版日期： 2014 出處： Technologies and Applications of Artificial Intelligence, 2014, Vol.8916, p.379-386 資源來源： Springer Books 版權： Springer International Publishing Switzerland 2014 識別號： ISSN: 0302-9743 識別號： ISBN: 331913986X 識別號： ISBN: 9783319139869 識別號： EISSN: 1611-3349 識別號： EISBN: 3319139878 識別號： EISBN: 9783319139876 識別號： DOI: 10.1007/978-3-319-13987-6_35 識別號： OCLC: 906028264 識別號： LCCallNum: Q334-342TJ210.2-211.
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	18	View/Open

社群 sharing

Loading...