Temporal Graph Attention Model for Enhanced Clinical Risk Prediction
R Bharath, P Sriram - 2024 IEEE International Students' …, 2024 - ieeexplore.ieee.org
Electronic health record (EHR)-based clinical risk prediction can help clinicians make better
decisions and understand early diagnosis. Nevertheless, accurate representations derived …
decisions and understand early diagnosis. Nevertheless, accurate representations derived …
Time-aware context-gated graph attention network for clinical risk prediction
Clinical risk prediction based on Electronic Health Records (EHR) can assist doctors in
better judgment and can make sense of early diagnosis. However, the prediction …
better judgment and can make sense of early diagnosis. However, the prediction …
Predictive Modeling with Temporal Graphical Representation on Electronic Health Records
Deep learning-based predictive models, leveraging Electronic Health Records (EHR), are
receiving increasing attention in healthcare. An effective representation of a patient's EHR …
receiving increasing attention in healthcare. An effective representation of a patient's EHR …
Self-supervised graph learning with hyperbolic embedding for temporal health event prediction
Electronic health records (EHRs) have been heavily used in modern healthcare systems for
recording patients' admission information to health facilities. Many data-driven approaches …
recording patients' admission information to health facilities. Many data-driven approaches …
Multi-gate Mixture of Multi-view Graph Contrastive Learning on Electronic Health Record
Y Cao, Q Wang, X Wang, D Peng… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Electronic Health Record (EHR) is the digital form of patient visits containing various medical
data, including diagnosis, treatment, and lab events. Representation learning of EHR with …
data, including diagnosis, treatment, and lab events. Representation learning of EHR with …
Interpretable time-aware and co-occurrence-aware network for medical prediction
C Sun, H Dui, H Li - BMC medical informatics and decision making, 2021 - Springer
Background Disease prediction based on electronic health records (EHRs) is essential for
personalized healthcare. But it's hard due to the special data structure and the …
personalized healthcare. But it's hard due to the special data structure and the …
Knowledge guided diagnosis prediction via graph spatial-temporal network
Predicting the future health conditions of patients based on Electronic Health Records (EHR)
is an important research topic. Due to the temporal nature of EHR data, the major challenge …
is an important research topic. Due to the temporal nature of EHR data, the major challenge …
Rapid Response System Based On Graph Attention Network For Forecasting Clinical Decline In EHR
B Sushma, SD Sree, MS Yadav - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Integrating electronic health records (EHR) with advanced predictive systems has
revolutionized healthcare by enabling early identification and intervention for patients at risk …
revolutionized healthcare by enabling early identification and intervention for patients at risk …
Time-aware Heterogeneous Graph Transformer with Adaptive Attention Merging for Health Event Prediction
S Li, H Cheng, R Li, W Li - arXiv preprint arXiv:2404.14815, 2024 - arxiv.org
The widespread application of Electronic Health Records (EHR) data in the medical field
has led to early successes in disease risk prediction using deep learning methods. These …
has led to early successes in disease risk prediction using deep learning methods. These …
[HTML][HTML] Graph learning with label attention and hyperbolic embedding for temporal event prediction in healthcare
The digitization of healthcare systems has led to the proliferation of electronic health records
(EHRs), serving as comprehensive repositories of patient information. However, the vast …
(EHRs), serving as comprehensive repositories of patient information. However, the vast …