A deep neural network using audio files for detection of aortic stenosis.

Voigt, Ingo; Boeckmann, Marc; Bruder, Oliver; Wolf, Alexander; Schmitz, Thomas; Wieneke, Heinrich

Voigt, Ingo; Boeckmann, Marc; Bruder, Oliver; Wolf, Alexander; Schmitz, Thomas; Wieneke, Heinrich.

Afiliação

Voigt I; Department of Cardiology and Angiology, Contilia Heart and Vascular Center, Elisabeth-Krankenhaus Essen, Essen, Germany.
Boeckmann M; Department of Cardiology and Angiology, Contilia Heart and Vascular Center, Elisabeth-Krankenhaus Essen, Essen, Germany.
Bruder O; Department of Cardiology and Angiology, Contilia Heart and Vascular Center, Elisabeth-Krankenhaus Essen, Essen, Germany.
Wolf A; Department of Cardiology and Angiology, Contilia Heart and Vascular Center, Elisabeth-Krankenhaus Essen, Essen, Germany.
Schmitz T; Department of Cardiology and Angiology, Contilia Heart and Vascular Center, Elisabeth-Krankenhaus Essen, Essen, Germany.
Wieneke H; Department of Cardiology and Angiology, Contilia Heart and Vascular Center, Elisabeth-Krankenhaus Essen, Essen, Germany.

Clin Cardiol ; 45(6): 657-663, 2022 Jun.

Article em En | MEDLINE | ID: mdl-35438211

Assuntos

Estenose da Valva Aórtica; Cardiologistas; Cardiologia; Estenose da Valva Aórtica/diagnóstico; Cardiologia/educação; Humanos; Redes Neurais de Computação; Projetos Piloto

Palavras-chave

aortic stenosis; artificial intelligence; auscultation; deep neural network; machine learning; valvular heart disease

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Estenose da Valva Aórtica / Cardiologia / Cardiologistas Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Clin Cardiol Ano de publicação: 2022 Tipo de documento: Article

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