Disease Outbreak Detection Using Search Keywords Patterns

I. Alsmadi, Zaid Almubaid, H. Al-Mubaid
{"title":"Disease Outbreak Detection Using Search Keywords Patterns","authors":"I. Alsmadi, Zaid Almubaid, H. Al-Mubaid","doi":"10.29007/z8tp","DOIUrl":null,"url":null,"abstract":"In the recent years, people are becoming more dependent on the Internet as their main source of information about healthcare. A number of research projects in the past few decades examined and utilized the internet data for information extraction in healthcare including disease surveillance and monitoring. In this paper, we investigate and study the potential of internet data like internet search keywords and search query patterns in the healthcare domain for disease monitoring and detection. Specifically, we investigate search keyword patterns for disease outbreak detection. Accurate prediction and detection of disease outbreaks in a timely manner can have a big positive impact on the entire health care system. Our method utilizes machine learning in identifying interesting patterns related to target disease outbreak from search keyword logs. We conducted experiments on the flu disease, which is the most searched disease in the interest of this problem. We showed examples of keywords that can be good predictors of outbreaks of the flu. Our method proved that the correlation between search queries and keyword trends are truly reliable in the sense that it can be used to predict the outbreak of the disease.","PeriodicalId":264035,"journal":{"name":"International Conference on Computers and Their Applications","volume":"810 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Computers and Their Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29007/z8tp","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

In the recent years, people are becoming more dependent on the Internet as their main source of information about healthcare. A number of research projects in the past few decades examined and utilized the internet data for information extraction in healthcare including disease surveillance and monitoring. In this paper, we investigate and study the potential of internet data like internet search keywords and search query patterns in the healthcare domain for disease monitoring and detection. Specifically, we investigate search keyword patterns for disease outbreak detection. Accurate prediction and detection of disease outbreaks in a timely manner can have a big positive impact on the entire health care system. Our method utilizes machine learning in identifying interesting patterns related to target disease outbreak from search keyword logs. We conducted experiments on the flu disease, which is the most searched disease in the interest of this problem. We showed examples of keywords that can be good predictors of outbreaks of the flu. Our method proved that the correlation between search queries and keyword trends are truly reliable in the sense that it can be used to predict the outbreak of the disease.
使用搜索关键字模式进行疾病爆发检测
近年来,人们越来越依赖互联网作为医疗保健信息的主要来源。在过去的几十年里,一些研究项目检查并利用互联网数据提取医疗保健方面的信息,包括疾病监测和监测。在本文中,我们调查和研究了互联网数据的潜力,如互联网搜索关键词和搜索查询模式在医疗保健领域的疾病监测和检测。具体来说,我们调查了疾病爆发检测的搜索关键字模式。准确预测和及时发现疾病爆发,可以对整个医疗保健系统产生巨大的积极影响。我们的方法利用机器学习从搜索关键字日志中识别与目标疾病爆发相关的有趣模式。为了研究这个问题,我们对搜索最多的流感疾病进行了实验。我们展示了一些关键词的例子,可以很好地预测流感的爆发。我们的方法证明了搜索查询和关键词趋势之间的相关性是真正可靠的,可以用来预测疾病的爆发。
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 求助全文
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:481959085
Book学术官方微信