Search Results for author:
Found 7 papers, 6 papers with code
Cohort-Individual Cooperative Learning for Multimodal Cancer Survival Analysis
In this paper, we propose a Cohort-individual Cooperative Learning (CCL) framework to advance cancer survival analysis by collaborating knowledge decomposition and cohort guidance.
iMD4GC: Incomplete Multimodal Data Integration to Advance Precise Treatment Response Prediction and Survival Analysis for Gastric Cancer
The limited availability of modalities for each patient would cause information loss, adversely affecting predictive accuracy.
Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology
Unlike existing works that focus on pre-training powerful feature extractor or designing sophisticated instance aggregator, R$^2$T is tailored to re-embed instance features online.
Cross-Modal Translation and Alignment for Survival Analysis
With the rapid advances in high-throughput sequencing technologies, the focus of survival analysis has shifted from examining clinical indicators to incorporating genomic profiles with pathological images.
Multiple Instance Learning Framework with Masked Hard Instance Mining for Whole Slide Image Classification
Moreover, the student is used to update the teacher with an exponential moving average (EMA), which in turn identifies new hard instances for subsequent training iterations and stabilizes the optimization.
Boosting Multi-Label Image Classification with Complementary Parallel Self-Distillation
Then, the MLIC models of fewer categories are trained with these sub-tasks in parallel for respectively learning the joint patterns and the category-specific patterns of labels.
Deep Semantic Dictionary Learning for Multi-label Image Classification
Compared with single-label image classification, multi-label image classification is more practical and challenging.
