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09/08/2023
Leveraging Prototype Patient Representations with Feature-Missing-Aware Calibration to Mitigate EHR Data Sparsity
Electronic Health Record (EHR) data frequently exhibits sparse character...
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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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06/07/2023
M^3Fair: Mitigating Bias in Healthcare Data through Multi-Level and Multi-Sensitive-Attribute Reweighting Method
In the data-driven artificial intelligence paradigm, models heavily rely...
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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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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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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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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