7 papers
Disentangled Multi-modal Learning of Histology and Transcriptomics for Cancer Characterization
Yupei Zhang, Xiaofei Wang, Anran Liu +2
Histopathology remains the gold standard for cancer diagnosis and prognosis. With the advent of transcriptome profiling, multi-modal learning combining transcriptomics with histolo…
Interpretable Multimodal Cancer Prototyping with Whole Slide Images and Incompletely Paired Genomics
Yupei Zhang, Yating Huang, Wanming Hu +3
Multimodal approaches that integrate histology and genomics hold strong potential for precision oncology. However, phenotypic and genotypic heterogeneity limits the quality of intr…
Joint Modelling Histology and Molecular Markers for Cancer Classification
Xiaofei Wang, Hanyu Liu, Yupei Zhang +6
Cancers are characterized by remarkable heterogeneity and diverse prognosis. Accurate cancer classification is essential for patient stratification and clinical decision-making. Al…
Long-tailed Medical Diagnosis with Relation-aware Representation Learning and Iterative Classifier Calibration
Li Pan, Yupei Zhang, Qiushi Yang +2
Recently computer-aided diagnosis has demonstrated promising performance, effectively alleviating the workload of clinicians. However, the inherent sample imbalance among different…
Focus on Focus: Focus-oriented Representation Learning and Multi-view Cross-modal Alignment for Glioma Grading
Li Pan, Yupei Zhang, Qiushi Yang +4
Recently, multimodal deep learning, which integrates histopathology slides and molecular biomarkers, has achieved a promising performance in glioma grading. Despite great progress,…
Knowledge-driven Subspace Fusion and Gradient Coordination for Multi-modal Learning
Yupei Zhang, Xiaofei Wang, Fangliangzi Meng +2
Multi-modal learning plays a crucial role in cancer diagnosis and prognosis. Current deep learning based multi-modal approaches are often limited by their abilities to model the co…