Comparing Deep Learning and Immunohistochemistry in Determining the Site of Origin for Well-Differentiated Neuroendocrine Tumors.

Redemann, Jordan; Schultz, Fred A; Martinez, Cathy; Harrell, Michael; Clark, Douglas P; Martin, David R; Hanson, Joshua A

Redemann, Jordan; Schultz, Fred A; Martinez, Cathy; Harrell, Michael; Clark, Douglas P; Martin, David R; Hanson, Joshua A.

Afiliação

Redemann J; Department of Pathology, University of New Mexico School of Medicine, Albuquerque, NM, USA.
Schultz FA; Department of Pathology, University of New Mexico School of Medicine, Albuquerque, NM, USA.
Martinez C; Department of Pathology, University of New Mexico School of Medicine, Albuquerque, NM, USA.
Harrell M; Department of Pathology, University of New Mexico School of Medicine, Albuquerque, NM, USA.
Clark DP; Department of Pathology, University of New Mexico School of Medicine, Albuquerque, NM, USA.
Martin DR; Department of Pathology, University of New Mexico School of Medicine, Albuquerque, NM, USA.
Hanson JA; Department of Pathology, University of New Mexico School of Medicine, Albuquerque, NM, USA.

J Pathol Inform ; 11: 32, 2020.

Article em En | MEDLINE | ID: mdl-33343993

Palavras-chave

Artificial Intelligence; convolutional neural network; deep learning; neuroendocrine tumor

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: J Pathol Inform Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

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