Please use this identifier to cite or link to this item: https://hdl.handle.net/10923/17280
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dc.contributor.authorPedro Moisés de Sousa-
dc.contributor.authorMarianne Modesto-
dc.contributor.authorGabrielle Macedo Pereira-
dc.contributor.authorCarlos Alberto da Costa Junior-
dc.contributor.authorLuís Vinícius de Moura-
dc.contributor.authorChristian Mattjie Oliveira-
dc.contributor.authorPedro Cunha Carneiro-
dc.contributor.authorAna Maria Marques da Silva-
dc.contributor.authorAna Cláudia Patrocínio-
dc.date.accessioned2021-06-02T17:22:56Z-
dc.date.available2021-06-02T17:22:56Z-
dc.date.issued2021-
dc.identifier.issn2446-4740-
dc.identifier.urihttps://hdl.handle.net/10923/17280-
dc.language.isoen-
dc.relation.ispartofRESEARCH ON BIOMEDICAL ENGINEERING-
dc.rightsopenAccess-
dc.subjectCOVID-
dc.subjectartificial neural networks-
dc.subjectartificial intelligence-
dc.titleCOVID-19 classification in X-ray chest images using a new convolutional neural network: CNN-COVID-
dc.typeArticle-
dc.date.updated2021-06-02T17:22:55Z-
dc.identifier.doiDOI:10.1007/s42600-020-00120-5-
dc.jtitleRESEARCH ON BIOMEDICAL ENGINEERING-
dc.volume37-
dc.issue1-
dc.spage1-
dc.epage12-
Appears in Collections:Artigo de Periódico



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