10 papers
What Is Missing in Surgical Risk Stratification and Outcome Prediction: A Scoping Review of End-to-End Machine Learning Approaches
Yizhi Dong, Yuhe Ke, Hairil Rizal Abdullah +4
Postoperative adverse events, including mortality and morbidity, remain a major global burden, many of which are preventable through early identification of high-risk patients and…
Evidential Fusion Network for Multimodal Survival Prediction under Missing Modalities
Yucheng Xing, Hailan Mo, Zi Wang +2
Recent multimodal survival prediction models have demonstrated strong predictive performance by leveraging complementary information across modalities. However, such models general…
Semantic-Anchored Evidential Fusion for Domain-Robust Whole-Slide Survival Analysis
Yucheng Xing, Ling Huang, Pei Liu +4
Whole-slide images (WSIs) are widely used for computational cancer prognosis. However, most existing methods primarily focus on in-domain performance and fail to generalize across…
DPsurv: Dual-Prototype Evidential Fusion for Uncertainty-Aware and Interpretable Whole-Slide Image Survival Prediction
Yucheng Xing, Ling Huang, Jingying Ma +6
Pathology whole-slide images (WSIs) are widely used for cancer survival analysis because of their comprehensive histopathological information at both cellular and tissue levels, en…
Bridging the Modality Bottleneck in Pathology MIL through Virtual Molecular Staining
Yucheng Xing, Pei Liu, Jingying Ma +6
Multiple instance learning (MIL) is the dominant framework for whole-slide image analysis in computational pathology, typically combining a frozen patch encoder, a projection layer…
Beyond Semantics: An Evidential Reasoning-Aware Multi-View Learning Framework for Trustworthy Mental Health Prediction
Yucheng Ruan, Ling Huang, Qika Lin +2
Automated mental health prediction using textual data has shown promising results with deep learning and large language models. However, deploying these models in high-stakes real-…