← Search

Joseph J. Y. Sung

2 accepted papers

2026

ConSurv: Multimodal Continual Learning for Survival Analysis

AAAI 2026technical

Survival prediction of cancers is crucial for clinical practice, as it informs mortality risks and influences treatment plans. However, a static model trained on a single dataset fails to adapt to the dynamically evolving clinical environment and continuous data streams, limiting its practical utili

Cited by 0SourcePDFScholar
2025

A Survey of Pathology Foundation Model: Progress and Future Directions

IJCAI 2025

Computational pathology, which involves analyzing whole slide images for automated cancer diagnosis, relies on multiple instance learning, where performance depends heavily on the feature extractor and aggregator. Recent Pathology Foundation Models (PFMs), pretrained on large-scale histopathology da