Please use this identifier to cite or link to this item: https://biore.bio.bg.ac.rs/handle/123456789/6875
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dc.contributor.authorMarkovic Sen_US
dc.contributor.authorRodic Aen_US
dc.contributor.authorMilicevic Oen_US
dc.contributor.authorSalom Ien_US
dc.contributor.authorDjordjevic Men_US
dc.contributor.authorDjordjevic Men_US
dc.date.accessioned2023-12-01T07:50:50Z-
dc.date.available2023-12-01T07:50:50Z-
dc.date.issued2023-06-
dc.identifier.urihttps://biore.bio.bg.ac.rs/handle/123456789/6875-
dc.publisherInstitute of Molecular Genetics and Genetic Engineering, University of Belgradeen_US
dc.titleMachine learning approach in inferring main population-level COVID-19 risk factorsen_US
dc.typeArticleen_US
dc.relation.conferenceBelgrade Bioinformatics Conference - BELBI, June 19 - 23, Belgrade, Serbiaen_US
dc.relation.publicationBook of Abstractsen_US
dc.description.rankM34en_US
dc.description.startpage58en_US
dc.relation.isbn978-86-82679-14-1en_US
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
crisitem.author.deptChair of General Physiology and Biophysics-
crisitem.author.deptChair of General Physiology and Biophysics-
crisitem.author.deptChair of General Physiology and Biophysics-
crisitem.author.orcid0000-0001-7506-500X-
crisitem.author.orcid0000-0003-2872-9066-
crisitem.author.orcid0000-0002-2903-3119-
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