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DEMoS: a deep learning-based ensemble approach for predicting the molecular subtypes of gastric adenocarcinomas from histopathological images.
Wang, Yanan; Hu, Changyuan; Kwok, Terry; Bain, Christopher A; Xue, Xiangyang; Gasser, Robin B; Webb, Geoffrey I; Boussioutas, Alex; Shen, Xian; Daly, Roger J; Song, Jiangning.
Afiliação
  • Wang Y; Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Melbourne 3800, Australia.
  • Hu C; Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Melbourne 3800, Australia.
  • Kwok T; Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Melbourne 3800, Australia.
  • Bain CA; Faculty of Information Technology, Monash University, Melbourne 3800, Australia.
  • Xue X; Department of General Surgery, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325027, China.
  • Gasser RB; Department of Veterinary Biosciences, Melbourne Veterinary School, The University of Melbourne, Parkville, VIC 3010, Australia.
  • Webb GI; Faculty of Information Technology, Monash Centre for Data Science, Monash University, Melbourne 3800, Australia.
  • Boussioutas A; Department of Data Science and Artificial Intelligence, Monash University, Melbourne, VIC 3800, Australia.
  • Shen X; The Alfred Hospital, Melbourne, VIC 3004, Australia.
  • Daly RJ; Central Clinical School, Monash University, Melbourne, VIC 3004, Australia.
  • Song J; Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Parkville, VIC 3010, Australia.
Bioinformatics ; 38(17): 4206-4213, 2022 09 02.
Article em En | MEDLINE | ID: mdl-35801909
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Gástricas / Adenocarcinoma / Aprendizado Profundo Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Austrália
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Gástricas / Adenocarcinoma / Aprendizado Profundo Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Austrália