机器学习与传染病预测:系统综述

IF 4 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Machine learning and knowledge extraction Pub Date : 2023-02-01 DOI:10.3390/make5010013
O. E. Santangelo, V. Gentile, Stefano Pizzo, D. Giordano, F. Cedrone
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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。
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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.
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CiteScore
6.30
自引率
0.00%
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0
审稿时长
7 weeks
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