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Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear...

Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5648794

Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images

About this item

Full title

Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images

Publisher

London: Nature Publishing Group UK

Journal title

Scientific reports, 2017-10, Vol.7 (1), p.13543-10, Article 13543

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Identification of patients with early stage non-small cell lung cancer (NSCLC) with high risk of recurrence could help identify patients who would receive additional benefit from adjuvant therapy. In this work, we present a computational histomorphometric image classifier using nuclear orientation, texture, shape, and tumor architecture to predict...

Alternative Titles

Full title

Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5648794

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5648794

Other Identifiers

ISSN

2045-2322

E-ISSN

2045-2322

DOI

10.1038/s41598-017-13773-7

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