4 citations · 13 across the 8 of their papers we have counts for
Showing eess.IVShow all
3 papers · 1 filter
eess.IV2024
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…
eess.IV2024★ 4 cited
iMD4GC: Incomplete Multimodal Data Integration to Advance Precise Treatment Response Prediction and Survival Analysis for Gastric Cancer
Fengtao Zhou, Yingxue Xu, Yanfen Cui +11
Gastric cancer (GC) is a prevalent malignancy worldwide, ranking as the fifth most common cancer with over 1 million new cases and 700 thousand deaths in 2020. Locally advanced gas…
eess.IV2023★ 4 cited
Cross-Modal Translation and Alignment for Survival Analysis
Fengtao Zhou, Hao Chen
With the rapid advances in high-throughput sequencing technologies, the focus of survival analysis has shifted from examining clinical indicators to incorporating genomic profiles…