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COVID-19 preVIEW: Semantic Search to Explore COVID-19 Research Preprints.
Langnickel, Lisa; Baum, Roman; Darms, Johannes; Madan, Sumit; Fluck, Juliane.
  • Langnickel L; ZB MED - Information Centre for Life Sciences, Cologne, Germany.
  • Baum R; Graduate School DILS, Bielefeld Institute for Bioinformatics Infrastructure (BIBI), Faculty of Technology, Bielefeld University, Bielefeld, Germany.
  • Darms J; ZB MED - Information Centre for Life Sciences, Cologne, Germany.
  • Madan S; ZB MED - Information Centre for Life Sciences, Cologne, Germany.
  • Fluck J; University of Bonn, Bonn, Germany.
Stud Health Technol Inform ; 281: 78-82, 2021 May 27.
Article in English | MEDLINE | ID: covidwho-1247788
ABSTRACT
During the current COVID-19 pandemic, the rapid availability of profound information is crucial in order to derive information about diagnosis, disease trajectory, treatment or to adapt the rules of conduct in public. The increased importance of preprints for COVID-19 research initiated the design of the preprint search engine preVIEW. Conceptually, it is a lightweight semantic search engine focusing on easy inclusion of specialized COVID-19 textual collections and provides a user friendly web interface for semantic information retrieval. In order to support semantic search functionality, we integrated a text mining workflow for indexing with relevant terminologies. Currently, diseases, human genes and SARS-CoV-2 proteins are annotated, and more will be added in future. The system integrates collections from several different preprint servers that are used in the biomedical domain to publish non-peer-reviewed work, thereby enabling one central access point for the users. In addition, our service offers facet searching, export functionality and an API access. COVID-19 preVIEW is publicly available at https//preview.zbmed.de.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Limits: Humans Language: English Journal: Stud Health Technol Inform Journal subject: Medical Informatics / Health Services Research Year: 2021 Document Type: Article Affiliation country: SHTI210124

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Limits: Humans Language: English Journal: Stud Health Technol Inform Journal subject: Medical Informatics / Health Services Research Year: 2021 Document Type: Article Affiliation country: SHTI210124