Detection and Visualisation of Pneumoconiosis Using an Ensemble of Multi-Dimensional Deep Features Learned from Chest X-rays.

Devnath, Liton; Fan, Zongwen; Luo, Suhuai; Summons, Peter; Wang, Dadong

Devnath, Liton; Fan, Zongwen; Luo, Suhuai; Summons, Peter; Wang, Dadong.

Afiliação

Devnath L; School of Information and Physical Sciences, The University of Newcastle, Newcastle 2308, Australia.
Fan Z; British Columbia Cancer Research Centre, Vancouver, BC V5Z 1L3, Canada.
Luo S; College of Computer Science and Technology, Huaqiao University, Xiamen 361021, China.
Summons P; School of Information and Physical Sciences, The University of Newcastle, Newcastle 2308, Australia.
Wang D; School of Information and Physical Sciences, The University of Newcastle, Newcastle 2308, Australia.

Int J Environ Res Public Health ; 19(18)2022 09 06.

Article em En | MEDLINE | ID: mdl-36141457

Assuntos

Pneumopatias; Pneumoconiose; Algoritmos; Poeira; Humanos; Pneumoconiose/diagnóstico por imagem; Raios X

Palavras-chave

CheXNet; Grad-CAM; chest X-ray radiographs; coal worker pneumoconiosis; computer-aided diagnosis; deep learning; ensemble learning; machine learning classifiers; occupational lung diseases; pneumoconiosis

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pneumoconiose / Pneumopatias Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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