4 papers
A Pathology Foundation Model for Gastric Cancer with Real-World Validation
Ling Liang, Jiabo Ma, Zhengyu Zhang +25
Gastric cancer remains a major cause of cancer mortality, yet its histological and molecular heterogeneity complicates diagnosis and risk stratification. General-purpose pathology…
LLM-driven Knowledge Enhancement for Multimodal Cancer Survival Prediction
Chenyu Zhao, Yingxue Xu, Fengtao Zhou +2
Current multimodal survival prediction methods typically rely on pathology images (WSIs) and genomic data, both of which are high-dimensional and redundant, making it difficult to…
Distilled Prompt Learning for Incomplete Multimodal Survival Prediction
Yingxue Xu, Fengtao Zhou, Chenyu Zhao +3
The integration of multimodal data including pathology images and gene profiles is widely applied in precise survival prediction. Despite recent advances in multimodal survival mod…
Cohort-Individual Cooperative Learning for Multimodal Cancer Survival Analysis
Huajun Zhou, Fengtao Zhou, Hao Chen
Recently, we have witnessed impressive achievements in cancer survival analysis by integrating multimodal data, e.g., pathology images and genomic profiles. However, the heterogene…