面向治疗方案的临床医学检索系统

Yuying Peng, W. Luo
{"title":"面向治疗方案的临床医学检索系统","authors":"Yuying Peng, W. Luo","doi":"10.1109/ICSCDE54196.2021.00028","DOIUrl":null,"url":null,"abstract":"In order to overcome the problem of low retrieval efficiency in the field of clinical medicine. According to the TREC evaluation task, the paper proposes a method for constructing a clinical medical retrieval system for treatment plan to improve retrieval efficiency, aiming at being able to obtain effective treatment options by entering patient-related information to facilitate the solution given by physicians or biomedical scientists. For the specificity of the dataset, this method considers genetic and demographic characteristics to preprocess documents and topics, and improve the query using the query expansion technique based on Medical Subject Headings (MeSH); Set up a Lucene-based retrieval system to read in the converted files, and get the primary feedback results by inputting the processed query into the retrieval, and then filter the result document to get the final result document. Experimental results show that this method can obtain documents with high relevance, which is of great significance to the field of clinical medicine information retrieval.","PeriodicalId":208108,"journal":{"name":"2021 International Conference of Social Computing and Digital Economy (ICSCDE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Clinical Medicine Retrieval System Oriented to Treatment Plan\",\"authors\":\"Yuying Peng, W. Luo\",\"doi\":\"10.1109/ICSCDE54196.2021.00028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to overcome the problem of low retrieval efficiency in the field of clinical medicine. According to the TREC evaluation task, the paper proposes a method for constructing a clinical medical retrieval system for treatment plan to improve retrieval efficiency, aiming at being able to obtain effective treatment options by entering patient-related information to facilitate the solution given by physicians or biomedical scientists. For the specificity of the dataset, this method considers genetic and demographic characteristics to preprocess documents and topics, and improve the query using the query expansion technique based on Medical Subject Headings (MeSH); Set up a Lucene-based retrieval system to read in the converted files, and get the primary feedback results by inputting the processed query into the retrieval, and then filter the result document to get the final result document. Experimental results show that this method can obtain documents with high relevance, which is of great significance to the field of clinical medicine information retrieval.\",\"PeriodicalId\":208108,\"journal\":{\"name\":\"2021 International Conference of Social Computing and Digital Economy (ICSCDE)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference of Social Computing and Digital Economy (ICSCDE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSCDE54196.2021.00028\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference of Social Computing and Digital Economy (ICSCDE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSCDE54196.2021.00028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

为了克服临床医学领域检索效率低的问题。根据TREC评价任务,本文提出了一种构建治疗方案临床医学检索系统的方法,以提高检索效率,旨在通过输入患者相关信息获得有效的治疗方案,方便医生或生物医学科学家给出解决方案。针对数据集的特殊性,该方法考虑遗传和人口统计学特征对文档和主题进行预处理,并利用基于医学主题词(MeSH)的查询扩展技术对查询进行改进;建立基于lucene的检索系统,读入转换后的文件,将处理后的查询输入到检索中,得到初步反馈结果,再对结果文档进行过滤,得到最终的结果文档。实验结果表明,该方法能够获得高相关度的文献,对临床医学信息检索领域具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Clinical Medicine Retrieval System Oriented to Treatment Plan
In order to overcome the problem of low retrieval efficiency in the field of clinical medicine. According to the TREC evaluation task, the paper proposes a method for constructing a clinical medical retrieval system for treatment plan to improve retrieval efficiency, aiming at being able to obtain effective treatment options by entering patient-related information to facilitate the solution given by physicians or biomedical scientists. For the specificity of the dataset, this method considers genetic and demographic characteristics to preprocess documents and topics, and improve the query using the query expansion technique based on Medical Subject Headings (MeSH); Set up a Lucene-based retrieval system to read in the converted files, and get the primary feedback results by inputting the processed query into the retrieval, and then filter the result document to get the final result document. Experimental results show that this method can obtain documents with high relevance, which is of great significance to the field of clinical medicine information retrieval.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信