Review of Machine Learning in Lung Ultrasound in COVID-19 Pandemic.

Wang, Jing; Yang, Xiaofeng; Zhou, Boran; Sohn, James J; Zhou, Jun; Jacob, Jesse T; Higgins, Kristin A; Bradley, Jeffrey D; Liu, Tian

Wang, Jing; Yang, Xiaofeng; Zhou, Boran; Sohn, James J; Zhou, Jun; Jacob, Jesse T; Higgins, Kristin A; Bradley, Jeffrey D; Liu, Tian.

Afiliación

Wang J; Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA.
Yang X; Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA.
Zhou B; Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA.
Sohn JJ; Department of Radiation Oncology, Virginia Commonwealth University, Richmond, VA 23219, USA.
Zhou J; Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA.
Jacob JT; Division of Infectious Diseases, Department of Medicine, Emory University, Atlanta, GA 30322, USA.
Higgins KA; Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA.
Bradley JD; Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA.
Liu T; Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA.

J Imaging ; 8(3)2022 Mar 05.

Article en En | MEDLINE | ID: mdl-35324620

Palabras clave

COVID-19; artificial intelligence (AI); deep learning; lung ultrasound; machine learning

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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies / Systematic_reviews Idioma: En Revista: J Imaging Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

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