Artificial intelligence for assistance of radiology residents in chest CT evaluation for COVID-19 pneumonia: a comparative diagnostic accuracy study.

Mlynska, Lucja; Malouhi, Amer; Ingwersen, Maja; Güttler, Felix; Gräger, Stephanie; Teichgräber, Ulf

Mlynska, Lucja; Malouhi, Amer; Ingwersen, Maja; Güttler, Felix; Gräger, Stephanie; Teichgräber, Ulf.

Afiliação

Mlynska L; Department for Diagnostic and Interventional Radiology, Friedrich-Schiller-University, University Hospital Jena, Jena, Germany.
Malouhi A; Department for Diagnostic and Interventional Radiology, Friedrich-Schiller-University, University Hospital Jena, Jena, Germany.
Ingwersen M; Department for Diagnostic and Interventional Radiology, Friedrich-Schiller-University, University Hospital Jena, Jena, Germany.
Güttler F; Department for Diagnostic and Interventional Radiology, Friedrich-Schiller-University, University Hospital Jena, Jena, Germany.
Gräger S; Department for Diagnostic and Interventional Radiology, Friedrich-Schiller-University, University Hospital Jena, Jena, Germany.
Teichgräber U; Department for Diagnostic and Interventional Radiology, Friedrich-Schiller-University, University Hospital Jena, Jena, Germany.

Acta Radiol ; 64(6): 2104-2110, 2023 Jun.

Article em En | MEDLINE | ID: mdl-36890698

Assuntos

COVID-19; Pneumonia; Radiologia; Humanos; Inteligência Artificial; Estudos de Casos e Controles; COVID-19/diagnóstico por imagem; Teste para COVID-19; Estudos Retrospectivos; SARS-CoV-2; Tomografia Computadorizada por Raios X/métodos

Palavras-chave

Artificial intelligence; COVID-19; SARS-CoV-2; computed tomography; deep learning; neural networks

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Pneumonia / Radiologia / COVID-19 Tipo de estudo: Diagnostic_studies / Observational_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google