Deep learning with robustness to missing data: A novel approach to the detection of COVID-19.

Çalli, Erdi; Murphy, Keelin; Kurstjens, Steef; Samson, Tijs; Herpers, Robert; Smits, Henk; Rutten, Matthieu; van Ginneken, Bram

Çalli, Erdi; Murphy, Keelin; Kurstjens, Steef; Samson, Tijs; Herpers, Robert; Smits, Henk; Rutten, Matthieu; van Ginneken, Bram.

Afiliación

Çalli E; Diagnostic Image Analysis Group, Radboudumc, Nijmegen, The Netherlands.
Murphy K; Diagnostic Image Analysis Group, Radboudumc, Nijmegen, The Netherlands.
Kurstjens S; Laboratory for Clinical Chemistry and Hematology, Jeroen Bosch Hospital, 's-Hertogenbosch, The Netherlands.
Samson T; Laboratory for Clinical Chemistry and Hematology, Jeroen Bosch Hospital, 's-Hertogenbosch, The Netherlands.
Herpers R; Laboratory for Clinical Chemistry and Hematology, Bernhoven Hospital, Uden, The Netherlands.
Smits H; Laboratory for Clinical Chemistry and Hematology, Bernhoven Hospital, Uden, The Netherlands.
Rutten M; Diagnostic Image Analysis Group, Radboudumc, Nijmegen, The Netherlands.
van Ginneken B; Department of Radiology, Jeroen Bosch Hospital, 's-Hertogenbosch, The Netherlands.

PLoS One ; 16(7): e0255301, 2021.

Article en En | MEDLINE | ID: mdl-34329354

Asunto(s)

Prueba de Ácido Nucleico para COVID-19; COVID-19/diagnóstico; Bases de Datos Factuales; Aprendizaje Profundo; Modelos Teóricos; SARS-CoV-2; Humanos; Distribución Aleatoria

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Bases de Datos Factuales / Aprendizaje Profundo / Prueba de Ácido Nucleico para COVID-19 / SARS-CoV-2 / COVID-19 / Modelos Teóricos Tipo de estudio: Clinical_trials / Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2021 Tipo del documento: Article País de afiliación: Países Bajos

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