6 papers
Sign-Constrained Intervention Effects for Domain-Generalizable ICU World Models
Zhen Xu, Nicholas Konz, Zhen Tan +2
Predicting how a patient's vital signs respond to an intervention is a central question in intensive care. World models can do so by learning dynamics as a function of prior action…
Aligning Multimodal Patient Evidence with Biomedical Knowledge Graphs for Clinical LLMs
Jiawen Du, Arshan Ali Khan, Chenhao Zhang +7
Clinical questions often depend on linking a patient's multimodal evidence to external biomedical knowledge, yet existing predictive systems rarely represent such links explicitly,…
On the Divergence of Accuracy and Mechanism Consistency in Time Series World Models
Haochen Zhang, Jiaheng Guo, Zhen Xu +4
A time series world model (TSWM) predicts a controlled system's state from its observed history and planned actions and exogenous inputs. Current approaches build forecasters with…
No Scale Left Behind: Multi-Scale Autoencoder with Bi-directional Attention for Time Series Anomaly Detection
Jiaheng Guo, Haochen Zhang, Yu-Chao Huang +3
Time series anomaly detection (TSAD) plays a crucial role in healthcare, finance, industrial monitoring, and other sectors. Within and between these settings, anomalies span vastly…
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…
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…