2 citations · 4 across the 12 of their papers we have counts for
13 papers
ZeroMAG: Zero-Shot Multimodal Adapter Generation for Plug-and-Play EEG Foundation Models
Yubo Wang, Jingying Ma, Xinliang Zhou +8
EEG foundation models (EFMs) capture reusable knowledge from large-scale EEG data, while many EEG recordings also include companion physiological signals that provide complementary…
Semantic-Anchored Evidential Fusion for Domain-Robust Whole-Slide Survival Analysis
Yucheng Xing, Ling Huang, Pei Liu +5
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…
CausalGuard: Conformal Inference under Graph Uncertainty
Vikash Singh, Weicong Chen, Debargha Ganguly +12
Estimating treatment effects from observational data requires choosing an adjustment set, but valid adjustment depends on an unknown causal graph. Graph misspecification can cause…
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…
Toward a Multi-View Brain Network Foundation Model: Cross-View Consistency Learning Across Arbitrary Atlases
Jiaxing Xu, Jingying Ma, Xin Lin +7
Brain network analysis provides an interpretable framework for characterizing brain organization and has been widely used for neurological disorder identification. Recent advances…
SCOPE: Structured Prototype-Guided Adaptation for EEG Foundation Models with Limited Labels
Jingying Ma, Feng Wu, Yucheng Xing +5
Electroencephalography (EEG) foundation models (EFMs) have shown strong potential for transferable representation learning, yet their adaptation in realistic settings remains chall…
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…
Toward Clinically Explainable AI for Medical Diagnosis: A Foundation Model with Human-Compatible Reasoning via Reinforcement Learning
Qika Lin, Yifan Zhu, Bin Pu +14
The clinical adoption of artificial intelligence (AI) in medical diagnostics is critically hampered by its black-box nature, which prevents clinicians from verifying the rationale…
CodeBrain: Bridging Decoupled Tokenizer and Multi-Scale Architecture for EEG Foundation Model
Jingying Ma, Feng Wu, Qika Lin +4
Electroencephalography (EEG) provides real-time insights into brain activity and supports diverse applications in neuroscience. While EEG foundation models (EFMs) have emerged to a…
Self-supervised Quantized Representation for Seamlessly Integrating Knowledge Graphs with Large Language Models
Qika Lin, Tianzhe Zhao, Kai He +5
Due to the presence of the natural gap between Knowledge Graph (KG) structures and the natural language, the effective integration of holistic structural information of KGs with La…
Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Survey
Qika Lin, Yifan Zhu, Xin Mei +6
The rapid development of artificial intelligence has constantly reshaped the field of intelligent healthcare and medicine. As a vital technology, multimodal learning has increasing…
Language Modeling on Tabular Data: A Survey of Foundations, Techniques and Evolution
Yucheng Ruan, Xiang Lan, Jingying Ma +3
Tabular data, a prevalent data type across various domains, presents unique challenges due to its heterogeneous nature and complex structural relationships. Achieving high predicti…
ST-USleepNet: A Spatial-Temporal Coupling Prominence Network for Multi-Channel Sleep Staging
Jingying Ma, Qika Lin, Ziyu Jia +1
Sleep staging is critical to assess sleep quality and diagnose disorders. Despite advancements in artificial intelligence enabling automated sleep staging, significant challenges r…