Yilan Zhang — accepted AI-conference papers

2026

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis

Yilan Zhang, Li Nanbo, Changchun Yang, Jürgen Schmidhuber, Xin Gao

ICLR 2026poster

The integration of histology images and gene profiles has shown great promise for improving survival prediction in cancer. However, current approaches often struggle to model intra- and inter-modal interactions efficiently and effectively due to the high dimensionality and complexity of the inputs.…

Cited by 0 Source ↗code ↗Scholar ↗

2024

Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction

Yilan Zhang, Yingxue Xu, Jianqi Chen, Fengying Xie, Hao Chen

ICLR 2024spotlight

Multimodal learning significantly benefits cancer survival prediction, especially the integration of pathological images and genomic data. Despite advantages of multimodal learning for cancer survival prediction, massive redundancy in multimodal data prevents it from extracting discriminative and co…

Cited by 38 Source ↗PDF ↗code ↗Scholar ↗