250 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Xiaoqian Jiang3 profiles5 · h 23
- Hua Xu3 profiles4 · h 7
- Jingcheng Du3 profiles4 · h 21
- Kirk Roberts3 profiles4 · h 36
- Rui Zhang3 profiles3 · h 77
- Yan Hu2 profiles3 · h 9
- Zhiyong Lu2 profiles3 · h 18
- Cui Tao2 profiles2 · h 30
- Fang Li2 profiles2 · h 12
- Jimin Huang2 profiles2 · h 19
- Kalpana Raja2 profiles2 · h 15
- Qingyu Chen2 profiles2 · h 32
- The University of Texas Health Science Center at HoustonUS15 papers
- Yale UniversityUS4 papers
- The University of Texas MD Anderson Cancer CenterUS3 papers
- National Institutes of HealthUS2 papers
- United States National Library of MedicineUS2 papers
- University of Maryland, BaltimoreUS2 papers
- Baylor College of MedicineUS1 paper
- Boston Children's HospitalUS1 paper
- Cornell UniversityUS1 paper
- Foundation for the National Institutes of HealthUS1 paper
- Harvard UniversityUS1 paper
- Houston MethodistUS1 paper
4 papers · 1 filter
A Generative Framework for Predictive Modeling of Multiple Chronic Conditions Using Graph Variational Autoencoder and Bandit-Optimized Graph Neural Network
Julian Carvajal Rico, Adel Alaeddini, Syed Hasib Akhter Faruqui +2
Predicting the emergence of multiple chronic conditions (MCC) is crucial for early intervention and personalized healthcare, as MCC significantly impacts patient outcomes and healt…
A Transformer-Based Deep Learning Approach for Fairly Predicting Post-Liver Transplant Risk Factors
Can Li, Xiaoqian Jiang, Kai Zhang
Liver transplantation is a life-saving procedure for patients with end-stage liver disease. There are two main challenges in liver transplant: finding the best matching patient for…
Deep Representation Learning of Patient Data from Electronic Health Records (EHR): A Systematic Review
Yuqi Si, Jingcheng Du, Zhao Li +5
Patient representation learning refers to learning a dense mathematical representation of a patient that encodes meaningful information from Electronic Health Records (EHRs). This…
Early Prediction of Acute Kidney Injury in Critical Care Setting Using Clinical Notes
Yikuan Li, Liang Yao, Chengsheng Mao +3
Acute kidney injury (AKI) in critically ill patients is associated with significant morbidity and mortality. Development of novel methods to identify patients with AKI earlier will…