5 papers
Sparse Task Vector Mixup with Hypernetworks for Efficient Knowledge Transfer in Whole-Slide Image Prognosis
Pei Liu, Xiangxiang Zeng, Tengfei Ma +3
Whole-Slide Images (WSIs) are widely used for estimating the prognosis of cancer patients. Current studies generally follow a cancer-specific learning paradigm. However, the availa…
Cross-Cancer Knowledge Transfer in WSI-based Prognosis Prediction
Pei Liu, Luping Ji, Jiaxiang Gou +1
Whole-Slide Image (WSI) is an important tool for estimating cancer prognosis. Current studies generally follow a conventional cancer-specific paradigm in which each cancer correspo…
Interpretable Vision-Language Survival Analysis with Ordinal Inductive Bias for Computational Pathology
Pei Liu, Luping Ji, Jiaxiang Gou +2
Histopathology Whole-Slide Images (WSIs) provide an important tool to assess cancer prognosis in computational pathology (CPATH). While existing survival analysis (SA) approaches h…
Queryable Prototype Multiple Instance Learning with Vision-Language Models for Incremental Whole Slide Image Classification
Jiaxiang Gou, Luping Ji, Pei Liu +1
Whole Slide Image (WSI) classification has very significant applications in clinical pathology, e.g., tumor identification and cancer diagnosis. Currently, most research attention…
Mining In-distribution Attributes in Outliers for Out-of-distribution Detection
Yutian Lei, Luping Ji, Pei Liu
Out-of-distribution (OOD) detection is indispensable for deploying reliable machine learning systems in real-world scenarios. Recent works, using auxiliary outliers in training, ha…