CGAT: Cell Graph ATtention Network for Grading of Pancreatic Disease Histology Images.

Baranwal, Mayank; Krishnan, Santhoshi; Oneka, Morgan; Frankel, Timothy; Rao, Arvind

Baranwal, Mayank; Krishnan, Santhoshi; Oneka, Morgan; Frankel, Timothy; Rao, Arvind.

Afiliação

Baranwal M; Division of Data & Decision Sciences, Tata Consultancy Services Research, Mumbai, India.
Krishnan S; Department of Systems and Control Engineering, Indian Institute of Technology, Bombay, India.
Oneka M; Department of Electrical & Computer Engineering, Rice University, Houston, TX, United States.
Frankel T; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States.
Rao A; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States.

Front Immunol ; 12: 727610, 2021.

Article em En | MEDLINE | ID: mdl-34671349

Assuntos

Modelos Teóricos; Pancreatopatias/classificação; Pancreatopatias/patologia; Adulto; Aprendizado Profundo; Feminino; Humanos; Masculino; Pessoa de Meia-Idade; Fenótipo

Palavras-chave

PDAC (pancreatic ductal adenocarcinoma); attention network; cell-graph; chronic pancreatitis; graph convolutional network (GCN); pancreas; spatial method

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Pancreatopatias / Modelos Teóricos Tipo de estudo: Prognostic_studies / Screening_studies Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Front Immunol Ano de publicação: 2021 Tipo de documento: Article

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