Automated detection of pneumonia in lung ultrasound using deep video classification for COVID-19.

Erfanian Ebadi, Salehe; Krishnaswamy, Deepa; Bolouri, Seyed Ehsan Seyed; Zonoobi, Dornoosh; Greiner, Russell; Meuser-Herr, Nathaniel; Jaremko, Jacob L; Kapur, Jeevesh; Noga, Michelle; Punithakumar, Kumaradevan

Erfanian Ebadi, Salehe; Krishnaswamy, Deepa; Bolouri, Seyed Ehsan Seyed; Zonoobi, Dornoosh; Greiner, Russell; Meuser-Herr, Nathaniel; Jaremko, Jacob L; Kapur, Jeevesh; Noga, Michelle; Punithakumar, Kumaradevan.

Afiliación

Erfanian Ebadi S; Department of Radiology & Diagnostic Imaging, University of Alberta, Edmonton, Canada.
Krishnaswamy D; MEDO.ai, Edmonton, Canada.
Bolouri SES; Servier Virtual Cardiac Centre, Mazankowski Alberta Heart Institute, Edmonton, Canada.
Zonoobi D; Department of Radiology & Diagnostic Imaging, University of Alberta, Edmonton, Canada.
Greiner R; Servier Virtual Cardiac Centre, Mazankowski Alberta Heart Institute, Edmonton, Canada.
Meuser-Herr N; MEDO.ai, Edmonton, Canada.
Jaremko JL; MEDO.ai, Edmonton, Canada.
Kapur J; Department of Computing Science, University of Alberta, Edmonton, Canada.
Noga M; Upstate Medical University, Syracuse, NY, USA.
Punithakumar K; Department of Radiology & Diagnostic Imaging, University of Alberta, Edmonton, Canada.

Inform Med Unlocked ; 25: 100687, 2021.

Article en En | MEDLINE | ID: mdl-34368420

Palabras clave

COVID-19; Convolutional neural networks; Lung ultrasound; Video classification

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Inform Med Unlocked Año: 2021 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Reino Unido

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