{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T11:48:36Z","timestamp":1753876116876,"version":"3.41.2"},"reference-count":31,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2022,10,5]],"date-time":"2022-10-05T00:00:00Z","timestamp":1664928000000},"content-version":"vor","delay-in-days":277,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1R35 GM141873-01"],"award-info":[{"award-number":["1R35 GM141873-01"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["2U24HG007822-08"],"award-info":[{"award-number":["2U24HG007822-08"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Proyectos I+D+i2020 -AI4PROFHEALTH","award":["PID2020-119266RA-I00"],"award-info":[{"award-number":["PID2020-119266RA-I00"]}]},{"name":"National Institutes of Health, Office of Research Infrastructure Programs","award":["R01OD010929"],"award-info":[{"award-number":["R01OD010929"]}]},{"DOI":"10.13039\/501100000024","name":"Canadian Institutes of Health Research","doi-asserted-by":"publisher","award":["FDN-167277"],"award-info":[{"award-number":["FDN-167277"]}],"id":[{"id":"10.13039\/501100000024","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,10,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The coronavirus disease 2019 (COVID-19) pandemic has compelled biomedical researchers to communicate data in real time to establish more effective medical treatments and public health policies. Nontraditional sources such as preprint publications, i.e. articles not yet validated by peer review, have become crucial hubs for the dissemination of scientific results. Natural language processing (NLP) systems have been recently developed to extract and organize COVID-19 data in reasoning systems. Given this scenario, the BioCreative COVID-19 text mining tool interactive demonstration track was created to assess the landscape of the available tools and to gauge user interest, thereby providing a two-way communication channel between NLP system developers and potential end users. The goal was to inform system designers about the performance and usability of their products and to suggest new additional features. Considering the exploratory nature of this track, the call for participation solicited teams to apply for the track, based on their system\u2019s ability to perform COVID-19-related tasks and interest in receiving user feedback. We also recruited volunteer users to test systems. Seven teams registered systems for the track, and &amp;gt;30 individuals volunteered as test users; these volunteer users covered a broad range of specialties, including bench scientists, bioinformaticians and biocurators. The users, who had the option to participate anonymously, were provided with written and video documentation to familiarize themselves with the NLP tools and completed a survey to record their evaluation. Additional feedback was also provided by NLP system developers. The track was well received as shown by the overall positive feedback from the participating teams and the users.<\/jats:p>\n               <jats:p>Database URL: https:\/\/biocreative.bioinformatics.udel.edu\/tasks\/biocreative-vii\/track-4\/<\/jats:p>","DOI":"10.1093\/database\/baac084","type":"journal-article","created":{"date-parts":[[2022,10,5]],"date-time":"2022-10-05T14:48:28Z","timestamp":1664981308000},"source":"Crossref","is-referenced-by-count":2,"title":["Overview of the COVID-19 text mining tool interactive demonstration track in BioCreative VII"],"prefix":"10.1093","volume":"2022","author":[{"given":"Andrew","family":"Chatr-aryamontri","sequence":"first","affiliation":[{"name":"Institute for Research in Immunology and Cancer (IRIC), University of Montreal , Marcelle-Coutu Pavilion, 2950 Chem. de Polytechnique Montreal, Quebec H3T 1J4, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8442-0720","authenticated-orcid":false,"given":"Lynette","family":"Hirschman","sequence":"additional","affiliation":[{"name":"MITRE Labs, The MITRE Corporation , 202 Burlington Rd., Bedford, MA 01730, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4633-6055","authenticated-orcid":false,"given":"Karen E","family":"Ross","sequence":"additional","affiliation":[{"name":"Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center , 2115 Wisconsin Ave NW, DC 20007, USA"}]},{"given":"Rose","family":"Oughtred","sequence":"additional","affiliation":[{"name":"Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University , South Drive, Princeton, NJ 08544, USA"}]},{"given":"Martin","family":"Krallinger","sequence":"additional","affiliation":[{"name":"Barcelona Supercomputing Center (BSC) , Pla\u00e7a d'Eusebi G\u00fcell, 1-3, Barcelona 08034, Spain"}]},{"given":"Kara","family":"Dolinski","sequence":"additional","affiliation":[{"name":"Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University , South Drive, Princeton, NJ 08544, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9713-9994","authenticated-orcid":false,"given":"Mike","family":"Tyers","sequence":"additional","affiliation":[{"name":"Institute for Research in Immunology and Cancer (IRIC), University of Montreal , Marcelle-Coutu Pavilion, 2950 Chem. de Polytechnique Montreal, Quebec H3T 1J4, Canada"}]},{"given":"Tonia","family":"Korves","sequence":"additional","affiliation":[{"name":"MITRE Labs, The MITRE Corporation , 202 Burlington Rd., Bedford, MA 01730, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0803-4817","authenticated-orcid":false,"given":"Cecilia N","family":"Arighi","sequence":"additional","affiliation":[{"name":"Computer and Information Sciences Department, University of Delaware , Ammon-Pinizzotto Biopharmaceutical Innovation Building, 590 Avenue 1743, Newark, DE 19713, USA"}]}],"member":"286","published-online":{"date-parts":[[2022,10,5]]},"reference":[{"key":"2022100513581516600_R1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-6-S1-S1","article-title":"Overview of BioCreAtIvE: critical assessment of information extraction for biology","volume":"6","author":"Hirschman","year":"2005","journal-title":"BMC Bioinform."},{"key":"2022100513581516600_R2","doi-asserted-by":"publisher","DOI":"10.1186\/gb-2008-9-s2-s2","article-title":"Overview of BioCreative II gene mention recognition","volume":"9","author":"Smith","year":"2008","journal-title":"Genome Biol."},{"key":"2022100513581516600_R3","doi-asserted-by":"publisher","DOI":"10.1186\/gb-2008-9-s2-s3","article-title":"Overview of BioCreative II gene normalization","volume":"9","author":"Morgan","year":"2008","journal-title":"Genome Biol."},{"key":"2022100513581516600_R4","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-12-S8-S2","article-title":"The gene normalization task in BioCreative III","volume":"12","author":"Lu","year":"2011","journal-title":"BMC Bioinform."},{"key":"2022100513581516600_R5","doi-asserted-by":"publisher","DOI":"10.1186\/1758-2946-7-S1-S2","article-title":"The CHEMDNER corpus of chemicals and drugs and its annotation principles","volume":"7","author":"Krallinger","year":"2015","journal-title":"J. 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