14 citations · 41 across the 14 of their papers we have counts for
6 papers · 1 filter
Redundancy-Free Self-Supervised Relational Learning for Graph Clustering
Si-Yu Yi, Wei Ju, Yifang Qin +4
Graph clustering, which learns the node representations for effective cluster assignments, is a fundamental yet challenging task in data analysis and has received considerable atte…
Towards Long-Tailed Recognition for Graph Classification via Collaborative Experts
Siyu Yi, Zhengyang Mao, Wei Ju +4
Graph classification, aiming at learning the graph-level representations for effective class assignments, has received outstanding achievements, which heavily relies on high-qualit…
Multi-task Learning via Adaptation to Similar Tasks for Mortality Prediction of Diverse Rare Diseases
Luchen Liu, Zequn Liu, Haoxian Wu +4
Mortality prediction of diverse rare diseases using electronic health record (EHR) data is a crucial task for intelligent healthcare. However, data insufficiency and the clinical d…
Predictive Multi-level Patient Representations from Electronic Health Records
Zichang Wang, Haoran Li, Luchen Liu +2
The advent of the Internet era has led to an explosive growth in the Electronic Health Records (EHR) in the past decades. The EHR data can be regarded as a collection of clinical e…
Early Prediction of Sepsis From Clinical Datavia Heterogeneous Event Aggregation
Luchen Liu, Haoxian Wu, Zichang Wang +2
Sepsis is a life-threatening condition that seriously endangers millions of people over the world. Hopefully, with the widespread availability of electronic health records (EHR), p…
Learning Hierarchical Representations of Electronic Health Records for Clinical Outcome Prediction
Luchen Liu, Haoran Li, Zhiting Hu +4
Clinical outcome prediction based on the Electronic Health Record (EHR) plays a crucial role in improving the quality of healthcare. Conventional deep sequential models fail to cap…