机器学习与传染病预测:系统综述

IF 4 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
O. E. Santangelo, V. Gentile, Stefano Pizzo, D. Giordano, F. Cedrone
{"title":"机器学习与传染病预测:系统综述","authors":"O. E. Santangelo, V. Gentile, Stefano Pizzo, D. Giordano, F. Cedrone","doi":"10.3390/make5010013","DOIUrl":null,"url":null,"abstract":"The aim of the study is to show whether it is possible to predict infectious disease outbreaks early, by using machine learning. This study was carried out following the guidelines of the Cochrane Collaboration and the meta-analysis of observational studies in epidemiology and the preferred reporting items for systematic reviews and meta-analyses. The suitable bibliography on PubMed/Medline and Scopus was searched by combining text, words, and titles on medical topics. At the end of the search, this systematic review contained 75 records. The studies analyzed in this systematic review demonstrate that it is possible to predict the incidence and trends of some infectious diseases; by combining several techniques and types of machine learning, it is possible to obtain accurate and plausible results.","PeriodicalId":93033,"journal":{"name":"Machine learning and knowledge extraction","volume":"3 1","pages":"175-198"},"PeriodicalIF":4.0000,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Machine Learning and Prediction of Infectious Diseases: A Systematic Review\",\"authors\":\"O. E. Santangelo, V. Gentile, Stefano Pizzo, D. Giordano, F. Cedrone\",\"doi\":\"10.3390/make5010013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of the study is to show whether it is possible to predict infectious disease outbreaks early, by using machine learning. This study was carried out following the guidelines of the Cochrane Collaboration and the meta-analysis of observational studies in epidemiology and the preferred reporting items for systematic reviews and meta-analyses. The suitable bibliography on PubMed/Medline and Scopus was searched by combining text, words, and titles on medical topics. At the end of the search, this systematic review contained 75 records. The studies analyzed in this systematic review demonstrate that it is possible to predict the incidence and trends of some infectious diseases; by combining several techniques and types of machine learning, it is possible to obtain accurate and plausible results.\",\"PeriodicalId\":93033,\"journal\":{\"name\":\"Machine learning and knowledge extraction\",\"volume\":\"3 1\",\"pages\":\"175-198\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2023-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Machine learning and knowledge extraction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/make5010013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Machine learning and knowledge extraction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/make5010013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 10

摘要

这项研究的目的是展示是否有可能通过使用机器学习来早期预测传染病的爆发。本研究遵循Cochrane协作网的指导方针和流行病学观察性研究的荟萃分析,以及系统评价和荟萃分析的首选报告项目。通过结合医学主题的文本、单词和标题,在PubMed/Medline和Scopus上搜索合适的书目。在搜索结束时,该系统综述包含75条记录。本系统综述分析的研究表明,对某些传染病的发病率和趋势进行预测是可能的;通过结合几种技术和类型的机器学习,可以获得准确和可信的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning and Prediction of Infectious Diseases: A Systematic Review
The aim of the study is to show whether it is possible to predict infectious disease outbreaks early, by using machine learning. This study was carried out following the guidelines of the Cochrane Collaboration and the meta-analysis of observational studies in epidemiology and the preferred reporting items for systematic reviews and meta-analyses. The suitable bibliography on PubMed/Medline and Scopus was searched by combining text, words, and titles on medical topics. At the end of the search, this systematic review contained 75 records. The studies analyzed in this systematic review demonstrate that it is possible to predict the incidence and trends of some infectious diseases; by combining several techniques and types of machine learning, it is possible to obtain accurate and plausible results.
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
CiteScore
6.30
自引率
0.00%
发文量
0
审稿时长
7 weeks
×
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