Fighting COVID-19 with computational tools: an AI guided review of 17,000 studies - The CSCoV database.

  • Francesco Napolitano (Creator)
  • Xiaopeng Xu (KAUST) (Creator)
  • Xin Gao (Creator)



CSCoV (Computational Studies about COVID-19) is a dataset containing COVID-19 related studies extracted from PubMed, bioRxiv, medRxiv, and arXiv, together with article and author related metrics obtained from Semantic Scholar (plus page views from bioRxiv and medRxiv). Using machine learning, the articles are categorized in six topics (Pharmacology, Genomics, Epidemiology, Healthcare, Clinical Medicine, Clinical Imaging) and prioritized. The database is periodically updated. Publication: TBA Files included in this release: cscov_09_2021.png: dataset statistics for the current CSCoV release. cscov_09_2021.tsv: CSCoV database. schema.json: metadata. cscov_09_2021.tar.gz: Doc2Vec and DeepWalk features used for the DL model Source code:
Date made availableSep 13 2021

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