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Prognostic analysis of histopathological images using pre-trained convolutional neural networks: app...

Prognostic analysis of histopathological images using pre-trained convolutional neural networks: app...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_07b9fe9bfd8d49948dbf283a3e7c6f76

Prognostic analysis of histopathological images using pre-trained convolutional neural networks: application to hepatocellular carcinoma

About this item

Full title

Prognostic analysis of histopathological images using pre-trained convolutional neural networks: application to hepatocellular carcinoma

Publisher

United States: PeerJ. Ltd

Journal title

PeerJ (San Francisco, CA), 2020-03, Vol.8, p.e8668, Article e8668

Language

English

Formats

Publication information

Publisher

United States: PeerJ. Ltd

More information

Scope and Contents

Contents

Histopathological images contain rich phenotypic descriptions of the molecular processes underlying disease progression. Convolutional neural networks, state-of-the-art image analysis techniques in computer vision, automatically learn representative features from such images which can be useful for disease diagnosis, prognosis, and subtyping. Hepat...

Alternative Titles

Full title

Prognostic analysis of histopathological images using pre-trained convolutional neural networks: application to hepatocellular carcinoma

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_07b9fe9bfd8d49948dbf283a3e7c6f76

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_07b9fe9bfd8d49948dbf283a3e7c6f76

Other Identifiers

ISSN

2167-8359

E-ISSN

2167-8359

DOI

10.7717/peerj.8668

How to access this item