COVID-Net USPro: An Explainable Few-Shot Deep Prototypical Network for COVID-19 Screening Using Point-of-Care Ultrasound.

Song, Jessy; Ebadi, Ashkan; Florea, Adrian; Xi, Pengcheng; Tremblay, Stéphane; Wong, Alexander

Song, Jessy; Ebadi, Ashkan; Florea, Adrian; Xi, Pengcheng; Tremblay, Stéphane; Wong, Alexander.

Afiliação

Song J; Department of Systems Design Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
Ebadi A; Department of Systems Design Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
Florea A; Digital Technologies Research Centre, National Research Council Canada, Toronto, ON M5T 3J1, Canada.
Xi P; Department of Emergency Medicine, McGill University, Montreal, QC H4A 3J1, Canada.
Tremblay S; Department of Systems Design Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
Wong A; Digital Technologies Research Centre, National Research Council Canada, Ottawa, ON K1A 0R6, Canada.

Sensors (Basel) ; 23(5)2023 Feb 27.

Article em En | MEDLINE | ID: mdl-36904833

Assuntos

COVID-19; Aprendizado Profundo; Inteligência Artificial; Teste para COVID-19; Sistemas Automatizados de Assistência Junto ao Leito; Reprodutibilidade dos Testes; SARS-CoV-2

Palavras-chave

COVID-19; deep explainable architecture; few-shot learning; lung; ultrasonic imaging

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo / COVID-19 Tipo de estudo: Diagnostic_studies / Prognostic_studies / Qualitative_research / Screening_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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