Deep learning for predicting prognostic consensus molecular subtypes in cervical cancer from histolo...
Deep learning for predicting prognostic consensus molecular subtypes in cervical cancer from histology images
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Publisher
London: Nature Publishing Group UK
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Language
English
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Publisher
London: Nature Publishing Group UK
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Contents
Cervical cancer remains the fourth most common cancer among women worldwide. This study proposes an end-to-end deep learning framework to predict consensus molecular subtypes (CMS) in HPV-positive cervical squamous cell carcinoma (CSCC) from H&E-stained histology slides. Analysing three CSCC cohorts (
n
= 545), we show our Digital-CMS scores...
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Full title
Deep learning for predicting prognostic consensus molecular subtypes in cervical cancer from histology images
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TN_cdi_doaj_primary_oai_doaj_org_article_dbb13d550312400e8168856157a1828a
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_dbb13d550312400e8168856157a1828a
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ISSN
2397-768X
E-ISSN
2397-768X
DOI
10.1038/s41698-024-00778-5
