Automated detection of acute respiratory distress syndrome from chest X-Rays using Directionality Measure and deep learning features.

Reamaroon, Narathip; Sjoding, Michael W; Gryak, Jonathan; Athey, Brian D; Najarian, Kayvan; Derksen, Harm

Reamaroon, Narathip; Sjoding, Michael W; Gryak, Jonathan; Athey, Brian D; Najarian, Kayvan; Derksen, Harm.

Afiliação

Reamaroon N; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States. Electronic address: nreamaro@umich.edu.
Sjoding MW; Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States.
Gryak J; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States.
Athey BD; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States.
Najarian K; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States.
Derksen H; Department of Mathematics, Northeastern University, Boston, MA, United States.

Comput Biol Med ; 134: 104463, 2021 07.

Article em En | MEDLINE | ID: mdl-33993014

Assuntos

Aprendizado Profundo; Síndrome do Desconforto Respiratório; Inteligência Artificial; Humanos; Reprodutibilidade dos Testes; Síndrome do Desconforto Respiratório/diagnóstico por imagem; Raios X

Palavras-chave

Acute respiratory distress syndrome; Chest X-ray images; Deep learning; Image processing; Machine learning

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Síndrome do Desconforto Respiratório / Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Humans Idioma: En Revista: Comput Biol Med Ano de publicação: 2021 Tipo de documento: Article

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