15 citations · 38 across the 10 of their papers we have counts for
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Dynamic voting in multi-view learning for radiomics applications
Hongliu Cao, Simon Bernard, Laurent Heutte +1
Cancer diagnosis and treatment often require a personalized analysis for each patient nowadays, due to the heterogeneity among the different types of tumor and among patients. Radi…
Improve the performance of transfer learning without fine-tuning using dissimilarity-based multi-view learning for breast cancer histology images
Hongliu Cao, Simon Bernard, Laurent Heutte +1
Breast cancer is one of the most common types of cancer and leading cancer-related death causes for women. In the context of ICIAR 2018 Grand Challenge on Breast Cancer Histology I…
Dissimilarity-based representation for radiomics applications
Hongliu Cao, Simon Bernard, Laurent Heutte +1
Radiomics is a term which refers to the analysis of the large amount of quantitative tumor features extracted from medical images to find useful predictive, diagnostic or prognosti…