Exploring non-invasive precision treatment in non-small cell lung cancer patients through deep learning radiomics across imaging features and molecular phenotypes

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Zhang, Xingping, Zhang, Guijuan, Qiu, Xingting, Yin, Jiao ORCID: 0000-0002-0269-2624, Tan, Wenjun, Yin, Xiaoxia, Yang, Hong, Wang, Hua ORCID: 0000-0002-8465-0996 and Zhang, Yanchun ORCID: 0000-0002-5094-5980 (2024) Exploring non-invasive precision treatment in non-small cell lung cancer patients through deep learning radiomics across imaging features and molecular phenotypes. Biomarker Research, 12. ISSN 2050-7771 (In Press)

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/48402
DOI 10.1186/s40364-024-00561-5
Official URL https://biomarkerres.biomedcentral.com/articles/10...
Subjects Current > FOR (2020) Classification > 3211 Oncology and carcinogenesis
Current > FOR (2020) Classification > 4611 Machine learning
Keywords deep learning; radiomics; actionable mutations; immune status; targeted therapy; immunotherapy; NSCLC
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