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Found 4 papers, 1 papers with code
MM-SurvNet: Deep Learning-Based Survival Risk Stratification in Breast Cancer Through Multimodal Data Fusion
Survival risk stratification is an important step in clinical decision making for breast cancer management.
BioFusionNet: Deep Learning-Based Survival Risk Stratification in ER+ Breast Cancer Through Multifeature and Multimodal Data Fusion
Here we present BioFusionNet, a deep learning framework that fuses image-derived features with genetic and clinical data to achieve a holistic patient profile and perform survival risk stratification of ER+ breast cancer patients.
hist2RNA: An efficient deep learning architecture to predict gene expression from breast cancer histopathology images
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).
Breast Cancer Histopathology Image based Gene Expression Prediction using Spatial Transcriptomics data and Deep Learning
Here we present BrST-Net, a deep learning framework for predicting gene expression from histopathology images using spatial transcriptomics data.
