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Evaluation of Wearable Acoustic Sensors and Machine Learning Algorithms for Automated Measurement of Left Ventricular Ejection Fraction.
Howard-Quijano, Kimberly; Saraf, Kanav; Borgstrom, Per; Baek, Christopher; Wasko, Michael; Zhang, Xu; Zheng, Yi; Saba, Samir; Mukkamala, Rama; Kaiser, William; Mahajan, Aman.
Afiliação
  • Howard-Quijano K; University of Pittsburgh Medical Center, Pittsburgh, Pensylvannia. Electronic address: khq@pitt.edu.
  • Saraf K; Samueli School of Engineering, University of California Los Angeles, Los Angeles, California.
  • Borgstrom P; Samueli School of Engineering, University of California Los Angeles, Los Angeles, California.
  • Baek C; Samueli School of Engineering, University of California Los Angeles, Los Angeles, California.
  • Wasko M; Samueli School of Engineering, University of California Los Angeles, Los Angeles, California.
  • Zhang X; Samueli School of Engineering, University of California Los Angeles, Los Angeles, California.
  • Zheng Y; Samueli School of Engineering, University of California Los Angeles, Los Angeles, California.
  • Saba S; University of Pittsburgh Medical Center, Pittsburgh, Pensylvannia.
  • Mukkamala R; University of Pittsburgh Medical Center, Pittsburgh, Pensylvannia.
  • Kaiser W; Samueli School of Engineering, University of California Los Angeles, Los Angeles, California.
  • Mahajan A; University of Pittsburgh Medical Center, Pittsburgh, Pensylvannia.
Am J Cardiol ; 200: 87-94, 2023 08 01.
Article em En | MEDLINE | ID: mdl-37307784
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Disfunção Ventricular Esquerda / Dispositivos Eletrônicos Vestíveis Tipo de estudo: Prognostic_studies Limite: Adult / Female / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Disfunção Ventricular Esquerda / Dispositivos Eletrônicos Vestíveis Tipo de estudo: Prognostic_studies Limite: Adult / Female / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article