A radiomics-boosted deep-learning model for COVID-19 and non-COVID-19 pneumonia classification using chest x-ray images.

Hu, Zongsheng; Yang, Zhenyu; Lafata, Kyle J; Yin, Fang-Fang; Wang, Chunhao

Hu, Zongsheng; Yang, Zhenyu; Lafata, Kyle J; Yin, Fang-Fang; Wang, Chunhao.

Afiliação

Hu Z; Medical Physics Graduate Program, Duke Kunshan University, Kunshan, Jiangsu, China.
Yang Z; Department of Radiation Oncology, Duke University, Durham, North Carolina, USA.
Lafata KJ; Department of Radiation Oncology, Duke University, Durham, North Carolina, USA.
Yin FF; Department of Radiology, Duke University, Durham, North Carolina, USA.
Wang C; Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina, USA.

Med Phys ; 49(5): 3213-3222, 2022 May.

Article em En | MEDLINE | ID: mdl-35263458

Assuntos

COVID-19; Aprendizado Profundo; COVID-19/diagnóstico por imagem; Humanos; Pandemias; SARS-CoV-2; Raios X

Palavras-chave

COVID-19; deep learning; radiomics; x-ray

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo / COVID-19 Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo / COVID-19 Idioma: En Ano de publicação: 2022 Tipo de documento: Article