Machine Learning and Knowledge Extraction (Feb 2023)

Machine Learning and Prediction of Infectious Diseases: A Systematic Review

  • Omar Enzo Santangelo,
  • Vito Gentile,
  • Stefano Pizzo,
  • Domiziana Giordano,
  • Fabrizio Cedrone

DOI
https://doi.org/10.3390/make5010013
Journal volume & issue
Vol. 5, no. 1
pp. 175 – 198

Abstract

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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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