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10.3233/SHTI210130

http://scihub22266oqcxt.onion/10.3233/SHTI210130
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34042715!ä!34042715

suck abstract from ncbi

pmid34042715      Stud+Health+Technol+Inform 2021 ; 281 (ä): 108-112
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  • Machine Learning to Identify Fake News for COVID-19 #MMPMID34042715
  • Isaakidou M; Zoulias E; Diomidous M
  • Stud Health Technol Inform 2021[May]; 281 (ä): 108-112 PMID34042715show ga
  • International Organizations are seriously concerned about the fake news phenomenon. UNESCO has defined the term of misinformation/disinformation, which are the two faces of fake news. European Commission has conducted a survey about "Fake News" through EU citizens to estimate the awareness and people behaviour related to the appearance of fake news and disinformation on electronic. The findings are quite worrying, since about 40% come across fake news daily and 85% evaluate fake news as a problem. The aim of this work is to introduce an Artificial Intelligence approach, the Decision Trees algorithm to identify fake news on the COVID-19.
  • |*COVID-19[MESH]
  • |Artificial Intelligence[MESH]
  • |Deception[MESH]
  • |Humans[MESH]
  • |Machine Learning[MESH]


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