63 citations · 151 across the 7 of their papers we have counts for
4 papers · 1 filter
Leveraging Vision-Language Embeddings for Zero-Shot Learning in Histopathology Images
Md Mamunur Rahaman, Ewan K. A. Millar, Erik Meijering
Zero-shot learning holds tremendous potential for histopathology image analysis by enabling models to generalize to unseen classes without extensive labeled data. Recent advancemen…
MM-SurvNet: Deep Learning-Based Survival Risk Stratification in Breast Cancer Through Multimodal Data Fusion
Raktim Kumar Mondol, Ewan K. A. Millar, Arcot Sowmya +1
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 integratin…
BioFusionNet: Deep Learning-Based Survival Risk Stratification in ER+ Breast Cancer Through Multifeature and Multimodal Data Fusion
Raktim Kumar Mondol, Ewan K. A. Millar, Arcot Sowmya +1
Breast cancer is a significant health concern affecting millions of women worldwide. Accurate survival risk stratification plays a crucial role in guiding personalised treatment de…
hist2RNA: An efficient deep learning architecture to predict gene expression from breast cancer histopathology images
Raktim Kumar Mondol, Ewan K. A. Millar, Peter H Graham +3
Gene expression can be used to subtype breast cancer with improved prediction of risk of recurrence and treatment responsiveness over that obtained using routine immunohistochemist…