89 citations · 123 across the 10 of their papers we have counts for
10 papers
Predict and Interpret Health Risk using EHR through Typical Patients
Zhihao Yu, Chaohe Zhang, Yasha Wang +3
Predicting health risks from electronic health records (EHR) is a topic of recent interest. Deep learning models have achieved success by modeling temporal and feature interaction.…
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…
CovidCare: Transferring Knowledge from Existing EMR to Emerging Epidemic for Interpretable Prognosis
Liantao Ma, Xinyu Ma, Junyi Gao +7
Due to the characteristics of COVID-19, the epidemic develops rapidly and overwhelms health service systems worldwide. Many patients suffer from systemic life-threatening problems…
Enabling Cost-Effective Population Health Monitoring By Exploiting Spatiotemporal Correlation: An Empirical Study
Dawei Chen, Jiangtao Wang, Wenjie Ruan +2
Because of its important role in health policy-shaping, population health monitoring (PHM) is considered a fundamental block for public health services. However, traditional public…
AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration
Liantao Ma, Junyi Gao, Yasha Wang +6
Deep learning-based health status representation learning and clinical prediction have raised much research interest in recent years. Existing models have shown superior performanc…
Multi-Label Robust Factorization Autoencoder and its Application in Predicting Drug-Drug Interactions
Xu Chu, Yang Lin, Jingyue Gao +3
Drug-drug interactions (DDIs) are a major cause of preventable hospitalizations and deaths. Predicting the occurrence of DDIs helps drug safety professionals allocate investigative…
Social-Network-Assisted Worker Recruitment in Mobile Crowd Sensing
Jiangtao Wang, Feng Wang, Yasha Wang +3
Worker recruitment is a crucial research problem in Mobile Crowd Sensing (MCS). While previous studies rely on a specified platform with a pre-assumed large user pool, this paper l…
HyTasker: Hybrid Task Allocation in Mobile Crowd Sensing
Jiangtao Wang, Feng Wang, Yasha Wang +5
Task allocation is a major challenge in Mobile Crowd Sensing (MCS). While previous task allocation approaches follow either the opportunistic or participatory mode, this paper prop…
Crowd-Powered Sensing and Actuation in Smart Cities: Current Issues and Future Directions
Jiangtao Wang, Yasha Wang, Daqing Zhang +2
With the advent of seamless connection of human, machine, and smart things, there is an emerging trend to leverage the power of crowds (e.g., citizens, mobile devices, and smart th…
Task Allocation in Mobile Crowd Sensing: State of the Art and Future Opportunities
Jiangtao Wang, Leye Wang, Yasha Wang +2
Mobile Crowd Sensing (MCS) is the special case of crowdsourcing, which leverages the smartphones with various embedded sensors and user's mobility to sense diverse phenomenon in a…