Radiomics under 2D regions, 3D regions, and peritumoral regions reveal tumor heterogeneity in non-small cell lung cancer: a multicenter study
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Zhang, Xingping, Zhang, Guijuan, Qiu, Xingting, Yin, Jiao ORCID: 0000-0002-0269-2624, Tan, Wenjun, Yin, Xiaoxia, Yang, Hong, Liao, Liefa, Wang, Hua ORCID: 0000-0002-8465-0996 and Zhang, Yanchun ORCID: 0000-0002-5094-5980 (2023) Radiomics under 2D regions, 3D regions, and peritumoral regions reveal tumor heterogeneity in non-small cell lung cancer: a multicenter study. La Radiologia Medica. ISSN 0033-8362
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Item type | Article |
URI | https://vuir.vu.edu.au/id/eprint/46774 |
DOI | 10.1007/s11547-023-01676-9 |
Official URL | https://link.springer.com/article/10.1007/s11547-0... |
Subjects | Current > FOR (2020) Classification > 4602 Artificial intelligence Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
Keywords | lung cancer, prognosis, cancer detection, radiomics |
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