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10.1016/j.procs.2020.09.287

http://scihub22266oqcxt.onion/10.1016/j.procs.2020.09.287
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suck abstract from ncbi


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pmid33042309      Procedia+Comput+Sci 2020 ; 176 (ä): 2287-2296
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  • Getting Insights from a Large Corpus of Scientific Papers on Specialisted Comprehensive Topics - the Case of COVID-19 #MMPMID33042309
  • Dousset B; Mothe J
  • Procedia Comput Sci 2020[]; 176 (ä): 2287-2296 PMID33042309show ga
  • COVID-19 is one of the most important topics these days, specifically on search engines and news. While fake news is easily shared, scientific papers are reliable sources where information can be extracted. With about 24,000 scientific publications on COVID-19 and related research on PubMed, automatic computer-assisted analysis is required. In this paper, we develop two methodologies to get insights on specific sub-topics of interest and latest research sub-topics. These rely on natural language processing and graph-based visualizations. We run these methodologies on two cases: the virus origin and the uses of existing drugs.
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