Fostering Natural Language Question Answering Over Knowledge Bases in Oncology EHR

M. A. Schwertner, S. Rigo, D. A. Araújo, Allan de Barcelos Silva, B. Eskofier
{"title":"Fostering Natural Language Question Answering Over Knowledge Bases in Oncology EHR","authors":"M. A. Schwertner, S. Rigo, D. A. Araújo, Allan de Barcelos Silva, B. Eskofier","doi":"10.1109/CBMS.2019.00102","DOIUrl":null,"url":null,"abstract":"This paper presents an approach for natural language question answering over a knowledge base generated by a medical texts information extraction process. The primary objective is to present a solution to help practitioners in oncology healthcare clinical environment with an intuitive method to access stored data. We identify health professional's needs in terms of information and interface with EHR systems. After that, we demonstrate a proposal to allow the integration of information extraction from clinical notes, knowledge base generation, and natural language question answering. The primary contributions are the identification of a solution to health professionals needs regarding usability in information access, and the demonstration of advantages obtained in representing health contents in a knowledge base.","PeriodicalId":311634,"journal":{"name":"2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.2019.00102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

This paper presents an approach for natural language question answering over a knowledge base generated by a medical texts information extraction process. The primary objective is to present a solution to help practitioners in oncology healthcare clinical environment with an intuitive method to access stored data. We identify health professional's needs in terms of information and interface with EHR systems. After that, we demonstrate a proposal to allow the integration of information extraction from clinical notes, knowledge base generation, and natural language question answering. The primary contributions are the identification of a solution to health professionals needs regarding usability in information access, and the demonstration of advantages obtained in representing health contents in a knowledge base.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
在肿瘤学电子病历知识库上培养自然语言问答
本文提出了一种基于医学文本信息提取过程生成的知识库的自然语言问答方法。主要目标是提供一种解决方案,帮助肿瘤医疗保健临床环境中的从业者使用直观的方法访问存储的数据。我们在信息和电子健康档案系统接口方面确定卫生专业人员的需求。之后,我们展示了一个建议,允许从临床记录中提取信息,知识库生成和自然语言问答的集成。主要贡献是确定了一种解决方案,以满足卫生专业人员在信息获取可用性方面的需求,并展示了在知识库中表示卫生内容所获得的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Analysing the Performance of a Real-Time Healthcare 4.0 System using Shared Frailty Time to Event Models Performance of Data Enhancements and Training Optimization for Neural Network: A Polyp Detection Case Study I Know How you Feel Now, and Here's why!: Demystifying Time-Continuous High Resolution Text-Based Affect Predictions in the Wild Identifying Diabetic Retinopathy from OCT Images using Deep Transfer Learning with Artificial Neural Networks Towards an Analysis of Post-Transcriptional Gene Regulation in Psoriasis via microRNAs using Machine Learning Algorithms
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1