PET/CT based cross-modal deep learning signature to predict occult nodal metastasis in lung cancer
PET/CT based cross-modal deep learning signature to predict occult nodal metastasis in lung cancer
About this item
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Author / Creator
Zhong, Yifan , Cai, Chuang , Chen, Tao , Gui, Hao , Deng, Jiajun , Yang, Minglei , Yu, Bentong , Song, Yongxiang , Wang, Tingting , Sun, Xiwen , Shi, Jingyun , Chen, Yangchun , Xie, Dong , Chen, Chang and She, Yunlang
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
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Publication information
Publisher
London: Nature Publishing Group UK
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Scope and Contents
Contents
Occult nodal metastasis (ONM) plays a significant role in comprehensive treatments of non-small cell lung cancer (NSCLC). This study aims to develop a deep learning signature based on positron emission tomography/computed tomography to predict ONM of clinical stage N0 NSCLC. An internal cohort (n = 1911) is included to construct the deep learning n...
Alternative Titles
Full title
PET/CT based cross-modal deep learning signature to predict occult nodal metastasis in lung cancer
Authors, Artists and Contributors
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_bd89d43617dd4e9e9206702ae1b48462
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_bd89d43617dd4e9e9206702ae1b48462
Other Identifiers
ISSN
2041-1723
E-ISSN
2041-1723
DOI
10.1038/s41467-023-42811-4
