Xiao-Guang Tu

Towards scalable cancer prognosis by aligning semi-supervised learning with survival modeling.

Prognostic assessment via whole-slide images (WSIs) is a key task in computational pathology. However, the development of robust predictive models is often bottlenecked by the scarcity of survival-annotated data, given the longitudinal nature of clinical follow-up. Despite its potential, semi-supervised learning (SSL)...