2 papers
cs.LG2024
DEDUCE: Multi-head attention decoupled contrastive learning to discover cancer subtypes based on multi-omics data
Liangrui Pan, Xiang Wang, Qingchun Liang +4
Background and Objective: Given the high heterogeneity and clinical diversity of cancer, substantial variations exist in multi-omics data and clinical features across different can…
cs.CV2024
SELECTOR: Heterogeneous graph network with convolutional masked autoencoder for multimodal robust prediction of cancer survival
Liangrui Pan, Yijun Peng, Yan Li +5
Accurately predicting the survival rate of cancer patients is crucial for aiding clinicians in planning appropriate treatment, reducing cancer-related medical expenses, and signifi…