11 papers
PatientWM: Towards Generalizable Clinical World Models via Unified Patient States
Ziwen Kan, Jie Peng, Bo Yan +5
Clinical decisions depend on anticipating how a patient's condition will evolve as treatment is adjusted and new evidence becomes available. Existing medical world models capture p…
Curriculum-Aware Interpolate-then-Refine: Learned Physiological Time-Series Imputation under Realistic Missingness
Yu-Chao Huang, Haochen Zhang, Nicholas Konz +1
Imputing physiological time series (arterial blood pressure, blood glucose, etc.) is essential for addressing the missingness that pervades clinical data. Yet modern imputation met…
CAST: Context- and Anomaly Structure-Conditioned Time Series Anomaly Generation
Haochen Zhang, Jie Peng, Songyuan Sui +3
Anomalous time series play a critical role in safety-critical domains, yet they are inherently scarce, heterogeneous, and costly to obtain. Existing time series generation methods…
GALA: Generation-Aware Cross-Modal Alignment for Text-to-Time-Series Synthesis
Haochen Zhang, Gengwei Zhang, Laura Yao +2
Synthesizing time series from natural language is emerging as the most expressive form of controllable time series generation. However, existing text-conditioned generators either…
Represent, Then Generate: Multimodal-Conditioned Time-Series Generation under Irregular Missingness
Haochen Zhang, Jiaheng Guo, Yu-Chao Huang +2
Continuous physiological time series underpin modern clinical monitoring, yet many of the most informative signals are invasive, expensive, or simply unavailable for a given patien…
PAMF: Prior-Aware Multimodal Fusion for Incomplete Time Series Data
Ziwen Kan, Wugeng Zheng, Tianlong Chen +1
In healthcare, multimodal time series tasks often operate on incomplete observations in practice, for example when ECG segments are lost because electrodes detach or an entire resp…
TRACE: A Temporal Conditional Estimation for Multimodal Time Series Foundation Models
Ziwen Kan, Yishuo Chen, Kecheng Li +7
Time series foundation models (TS-FMs) aim to learn generalizable temporal representations that can be adapted to a wide range of downstream tasks. In real-world multimodal setting…
ConceptMoE: Concept-Guided Multimodal Mixture of Experts for Interpretable Computational Pathology
Xuan Wang, Zhongling Xu, Gopi Kannedhara +13
Healthcare models are transitioning from unimodal prediction toward multimodal reasoning over heterogeneous diagnostic inputs. In computational pathology, for complex tumor subtype…
Detecting Unfaithful Chain-of-Thought via Circuit-Guided Internal-External Discrepancy
Xu Shen, Zhen Tan, Song Wang +4
Chain-of-thought (CoT) reasoning improves the problem-solving ability of large language models (LLMs), but generated reasoning traces may not faithfully reflect the model's actual…
MuteBench: Modality Unavailability Tolerance Evaluation for Incomplete Multimodal Fusion
Wugeng Zheng, Ziwen Kan, Tianlong Chen +3
Multimodal physiological data powers clinical AI systems from intensive care units to wearable devices, but sensors routinely fail in practice. Two failure modes are common: modali…
Interpretable Alzheimer's Diagnosis via Multimodal Fusion of Regional Brain Experts
Farica Zhuang, Shu Yang, Dinara Aliyeva +6
Accurate and early diagnosis of Alzheimer's disease (AD) is critical for effective intervention and requires integrating complementary information from multimodal neuroimaging data…