89 citations · 93 across the 7 of their papers we have counts for
8 papers · 1 filter
SMART: Towards Pre-trained Missing-Aware Model for Patient Health Status Prediction
Zhihao Yu, Xu Chu, Yujie Jin +2
Electronic health record (EHR) data has emerged as a valuable resource for analyzing patient health status. However, the prevalence of missing data in EHR poses significant challen…
Imputation with Inter-Series Information from Prototypes for Irregular Sampled Time Series
Zhihao Yu, Xu Chu, Liantao Ma +2
Irregularly sampled time series are ubiquitous, presenting significant challenges for analysis due to missing values. Despite existing methods address imputation, they predominantl…
Learnable Prompt as Pseudo-Imputation: Rethinking the Necessity of Traditional EHR Data Imputation in Downstream Clinical Prediction
Weibin Liao, Yinghao Zhu, Zhongji Zhang +5
Analyzing the health status of patients based on Electronic Health Records (EHR) is a fundamental research problem in medical informatics. The presence of extensive missing values…
Fused Gromov-Wasserstein Graph Mixup for Graph-level Classifications
Xinyu Ma, Xu Chu, Yasha Wang +4
Graph data augmentation has shown superiority in enhancing generalizability and robustness of GNNs in graph-level classifications. However, existing methods primarily focus on the…
MCare: Learning with Missing Modalities in Multimodal Healthcare Data
Chaohe Zhang, Xu Chu, Liantao Ma +4
Multimodal electronic health record (EHR) data are widely used in clinical applications. Conventional methods usually assume that each sample (patient) is associated with the unifi…
Domain Generalization through the Lens of Angular Invariance
Yujie Jin, Xu Chu, Yasha Wang +1
Domain generalization (DG) aims at generalizing a classifier trained on multiple source domains to an unseen target domain with domain shift. A common pervasive theme in existing D…