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20192024
most citedSepsisLab: Early Sepsis Prediction with Uncertainty Quantification and Active Sensing

46 citations · 52 across the 8 of their papers we have counts for

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cs.LG202446 cited

SepsisLab: Early Sepsis Prediction with Uncertainty Quantification and Active Sensing

Changchang Yin, Pin-Yu Chen, Bingsheng Yao +3

Sepsis is the leading cause of in-hospital mortality in the USA. Early sepsis onset prediction and diagnosis could significantly improve the survival of sepsis patients. Existing p…

cs.LG2022

Deconfounding Actor-Critic Network with Policy Adaptation for Dynamic Treatment Regimes

Changchang Yin, Ruoqi Liu, Jeffrey Caterino +1

Despite intense efforts in basic and clinical research, an individualized ventilation strategy for critically ill patients remains a major challenge. Recently, dynamic treatment re…

cs.LG2021

Temporal Clustering with External Memory Network for Disease Progression Modeling

Zicong Zhang, Changchang Yin, Ping Zhang

Disease progression modeling (DPM) involves using mathematical frameworks to quantitatively measure the severity of how certain disease progresses. DPM is useful in many ways such…

cs.LG2021

Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task Learning

Thai-Hoang Pham, Changchang Yin, Laxmi Mehta +2

Complication risk profiling is a key challenge in the healthcare domain due to the complex interaction between heterogeneous entities (e.g., visit, disease, medication) in clinical…

cs.LG2020

Interpretable Deep Learning for Automatic Diagnosis of 12-lead Electrocardiogram

Dongdong Zhang, Xiaohui Yuan, Ping Zhang

Electrocardiogram (ECG) is a widely used reliable, non-invasive approach for cardiovascular disease diagnosis. With the rapid growth of ECG examinations and the insufficiency of ca…

cs.LG2019

Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations

Xiang Yue, Zhen Wang, Jingong Huang +7

Graph embedding learning that aims to automatically learn low-dimensional node representations, has drawn increasing attention in recent years. To date, most recent graph embedding…