Evaluation of Hemodialysis Arteriovenous Bruit by Deep Learning.

Ota, Keisuke; Nishiura, Yousuke; Ishihara, Saki; Adachi, Hihoko; Yamamoto, Takehisa; Hamano, Takayuki

Ota, Keisuke; Nishiura, Yousuke; Ishihara, Saki; Adachi, Hihoko; Yamamoto, Takehisa; Hamano, Takayuki.

Ota K; Department of Nephrology, Gamagori City Hospital, Gamagori 443-8501, Japan.
Nishiura Y; Department of Medical Engineering, Gamagori City Hospital, Gamagori 443-8501, Japan.
Ishihara S; Department of Medical Engineering, Gamagori City Hospital, Gamagori 443-8501, Japan.
Adachi H; Department of Medical Engineering, Gamagori City Hospital, Gamagori 443-8501, Japan.
Yamamoto T; Department of Medical Engineering, Gamagori City Hospital, Gamagori 443-8501, Japan.
Hamano T; Department of Nephrology, Nagoya City University Graduate School of Medical Sciences, Nagoya 467-8601, Japan.

Sensors (Basel) ; 20(17)2020 Aug 27.

Article en En | MEDLINE | ID: mdl-32867220

Asunto(s)

Fístula Arteriovenosa; Auscultación; Aprendizaje Profundo; Diálisis Renal; Anciano; Anciano de 80 o más Años; Femenino; Humanos; Masculino; Persona de Mediana Edad; Redes Neurales de la Computación; Curva ROC

Palabras clave

arteriovenous fistula; artificial intelligence; auscultation; convolutional neural network; deep learning; hemodialysis patient; shunt sound

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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Auscultación / Fístula Arteriovenosa / Diálisis Renal / Aprendizaje Profundo Tipo de estudio: Prognostic_studies Límite: Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Año: 2020 Tipo del documento: Article

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