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pro vyhledávání: '"Mondol, Raktim Kumar"'
Survival risk stratification is an important step in clinical decision making for breast cancer management. We propose a novel deep learning approach for this purpose by integrating histopathological imaging, genetic and clinical data. It employs vis
Externí odkaz:
http://arxiv.org/abs/2402.11788
Publikováno v:
JBHI, 24 June 2024
Breast cancer is a significant health concern affecting millions of women worldwide. Accurate survival risk stratification plays a crucial role in guiding personalised treatment decisions and improving patient outcomes. Here we present BioFusionNet,
Externí odkaz:
http://arxiv.org/abs/2402.10717
Autor:
Mondol, Raktim Kumar, Millar, Ewan K. A., Graham, Peter H, Browne, Lois, Sowmya, Arcot, Meijering, Erik
Gene expression can be used to subtype breast cancer with improved prediction of risk of recurrence and treatment responsiveness over that obtained using routine immunohistochemistry (IHC). However, in the clinic, molecular profiling is primarily use
Externí odkaz:
http://arxiv.org/abs/2304.04507
Akademický článek
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Publikováno v:
2015 International Conference on Advances in Computer Engineering & Applications; 2015, p993-996, 4p
Publikováno v:
2015 International Conference on Advances in Computer Engineering & Applications; 2015, p988-992, 5p
Publikováno v:
2015 International Conference on Advanced Computing & Communication Systems; 2015, p1-4, 4p
Publikováno v:
2015 3rd International Conference on Green Energy & Technology (ICGET); 2015, p1-4, 4p
Publikováno v:
2015 International Conference on Innovations in Information, Embedded & Communication Systems (ICIIECS); 2015, p1-5, 5p
Publikováno v:
2015 IEEE International Conference on Electrical, Computer & Communication Technologies (ICECCT); 2015, p1-5, 5p