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Performance of a Convolutional Neural Network and Explainability Technique for 12-Lead Electrocardiogram Interpretation.
Hughes, J Weston; Olgin, Jeffrey E; Avram, Robert; Abreau, Sean A; Sittler, Taylor; Radia, Kaahan; Hsia, Henry; Walters, Tomos; Lee, Byron; Gonzalez, Joseph E; Tison, Geoffrey H.
Afiliación
  • Hughes JW; RISE Lab, Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley.
  • Olgin JE; Department of Medicine, Division of Cardiology, University of California, San Francisco, San Francisco.
  • Avram R; Cardiovascular Research Institute, San Francisco, California.
  • Abreau SA; Department of Medicine, Division of Cardiology, University of California, San Francisco, San Francisco.
  • Sittler T; Cardiovascular Research Institute, San Francisco, California.
  • Radia K; Department of Medicine, Division of Cardiology, University of California, San Francisco, San Francisco.
  • Hsia H; Cardiovascular Research Institute, San Francisco, California.
  • Walters T; Department of Laboratory Medicine, University of California, San Francisco, San Francisco.
  • Lee B; RISE Lab, Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley.
  • Gonzalez JE; Department of Medicine, Division of Cardiology, University of California, San Francisco, San Francisco.
  • Tison GH; Department of Medicine, Division of Cardiology, University of California, San Francisco, San Francisco.
JAMA Cardiol ; 6(11): 1285-1295, 2021 11 01.
Article en En | MEDLINE | ID: mdl-34347007
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Algoritmos / Enfermedades Cardiovasculares / Redes Neurales de la Computación / Consenso / Electrocardiografía / Aprendizaje Automático / Frecuencia Cardíaca Tipo de estudio: Guideline / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Male / Middle aged Idioma: En Revista: JAMA Cardiol Año: 2021 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Algoritmos / Enfermedades Cardiovasculares / Redes Neurales de la Computación / Consenso / Electrocardiografía / Aprendizaje Automático / Frecuencia Cardíaca Tipo de estudio: Guideline / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Male / Middle aged Idioma: En Revista: JAMA Cardiol Año: 2021 Tipo del documento: Article