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06/28/2023
Graph Interpolation via Fast Fused-Gromovization
Graph data augmentation has proven to be effective in enhancing the gene...
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01/17/2023
Mortality Prediction with Adaptive Feature Importance Recalibration for Peritoneal Dialysis Patients: a deep-learning-based study on a real-world longitudinal follow-up dataset
Objective: Peritoneal Dialysis (PD) is one of the most widely used life-...
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10/28/2022
M^3Care: Learning with Missing Modalities in Multimodal Healthcare Data
Multimodal electronic health record (EHR) data are widely used in clinic...
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10/28/2022
Domain Generalization through the Lens of Angular Invariance
Domain generalization (DG) aims at generalizing a classifier trained on ...
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09/16/2022
A Comprehensive Benchmark for COVID-19 Predictive Modeling Using Electronic Health Records in Intensive Care: Choosing the Best Model for COVID-19 Prognosis
The COVID-19 pandemic has posed a heavy burden to the healthcare system ...
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04/21/2022
MedFACT: Modeling Medical Feature Correlations in Patient Health Representation Learning via Feature Clustering
In healthcare prediction tasks, it is essential to exploit the correlati...
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12/07/2020
SpotTune: Leveraging Transient Resources for Cost-efficient Hyper-parameter Tuning in the Public Cloud
Hyper-parameter tuning (HPT) is crucial for many machine learning (ML) a...
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07/17/2020
CovidCare: Transferring Knowledge from Existing EMR to Emerging Epidemic for Interpretable Prognosis
Due to the characteristics of COVID-19, the epidemic develops rapidly an...
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01/24/2020
StageNet: Stage-Aware Neural Networks for Health Risk Prediction
Deep learning has demonstrated success in health risk prediction especia...
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11/27/2019
ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context
Predicting the patient's clinical outcome from the historical electronic...
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11/27/2019
AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration
Deep learning-based health status representation learning and clinical p...
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03/18/2019
MUSEFood: Multi-sensor-based Food Volume Estimation on Smartphones
Researches have shown that diet recording can help people increase aware...
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11/01/2018
Multi-Label Robust Factorization Autoencoder and its Application in Predicting Drug-Drug Interactions
Drug-drug interactions (DDIs) are a major cause of preventable hospitali...
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09/08/2018
CrowdExpress: A Probabilistic Framework for On-Time Crowdsourced Package Deliveries
Speed and cost of logistics are two major concerns to on-line shoppers, ...
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05/22/2018
Social-Network-Assisted Worker Recruitment in Mobile Crowd Sensing
Worker recruitment is a crucial research problem in Mobile Crowd Sensing...
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05/22/2018
HyTasker: Hybrid Task Allocation in Mobile Crowd Sensing
Task allocation is a major challenge in Mobile Crowd Sensing (MCS). Whil...
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05/22/2018
Crowd-Powered Sensing and Actuation in Smart Cities: Current Issues and Future Directions
With the advent of seamless connection of human, machine, and smart thin...
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05/22/2018
Task Allocation in Mobile Crowd Sensing: State of the Art and Future Opportunities
Mobile Crowd Sensing (MCS) is the special case of crowdsourcing, which l...
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04/19/2018
Cell Selection with Deep Reinforcement Learning in Sparse Mobile Crowdsensing
Sparse Mobile CrowdSensing (MCS) is a novel MCS paradigm where data infe...
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09/14/2017