Author

Linghan Cai

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Oct 2026

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)...

Yi Huang, Ling-Han Cai, Zi-Liang Feng et al. · Medical Image Analysis · 0 citations

Review Aug 2026

Agentic Visual Reasoning in Whole-Slide Pathology Images via Active Perception

Whole-slide visual reasoning requires identifying sparse diagnostic evidence in gigapixel pathology slides and integrating observations across spatial scales. Existing WSI methods either compress densely sampled patches into global representations or use pretrained vision-language models with heuristic region selection...

Jing-Yun Chen, Feng-Chun Liu, Linghan Cai et al. · 1 citation