17 citations · 44 across the 6 of their papers we have counts for
6 papers
Towards Trustworthy Explanation: On Causal Rationalization
Wenbo Zhang, Tong Wu, Yunlong Wang +2
With recent advances in natural language processing, rationalization becomes an essential self-explaining diagram to disentangle the black box by selecting a subset of input texts…
FD-GATDR: A Federated-Decentralized-Learning Graph Attention Network for Doctor Recommendation Using EHR
Luning Bi, Yunlong Wang, Fan Zhang +3
In the past decade, with the development of big data technology, an increasing amount of patient information has been stored as electronic health records (EHRs). Leveraging these d…
Predicting Treatment Initiation from Clinical Time Series Data via Graph-Augmented Time-Sensitive Model
Fan Zhang, Tong Wu, Yunlong Wang +5
Many computational models were proposed to extract temporal patterns from clinical time series for each patient and among patient group for predictive healthcare. However, the comm…
Rare Disease Detection by Sequence Modeling with Generative Adversarial Networks
Kezi Yu, Yunlong Wang, Yong Cai +4
Rare diseases affecting 350 million individuals are commonly associated with delay in diagnosis or misdiagnosis. To improve those patients' outcome, rare disease detection is an im…
Semi-supervised Rare Disease Detection Using Generative Adversarial Network
Wenyuan Li, Yunlong Wang, Yong Cai +3
Rare diseases affect a relatively small number of people, which limits investment in research for treatments and cures. Developing an efficient method for rare disease detection is…
Rare Disease Physician Targeting: A Factor Graph Approach
Yong Cai, Yunlong Wang, Dong Dai
In rare disease physician targeting, a major challenge is how to identify physicians who are treating diagnosed or underdiagnosed rare diseases patients. Rare diseases have extreme…