DHGL: Dynamic hypergraph‐based deep learning model for disease prediction
Electronic health record (EHR) data is crucial in providing comprehensive historical disease
information for patients and is frequently utilized in health event prediction. However, current …
information for patients and is frequently utilized in health event prediction. However, current …
Ehr2hg: Modeling of ehrs data based on hypergraphs for disease prediction
Z Sun, X Yang, Z Feng, T Xu, X Fan… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
EHRs contain the patient's historical disease information, and a natural idea is to predict the
patient's disease or diagnose the patient based on EHRs. However, existing deep learning …
patient's disease or diagnose the patient based on EHRs. However, existing deep learning …
DEEP NEURAL NETWORKS FOR COMPLEX DISEASE PREDICTION USING ELECTRONIC HEALTH RECORDS AND GENOMIC DATA
H Javidi - 2024 - rave.ohiolink.edu
Leveraging electronic health record data requires sophisticated methods that can optimally
process this information to improve clinical decision-making. Artificial Intelligence (AI) …
process this information to improve clinical decision-making. Artificial Intelligence (AI) …
Context-aware health event prediction via transition functions on dynamic disease graphs
With the wide application of electronic health records (EHR) in healthcare facilities, health
event prediction with deep learning has gained more and more attention. A common feature …
event prediction with deep learning has gained more and more attention. A common feature …
Stage-aware hierarchical attentive relational network for diagnosis prediction
Recently, Electronic Health Records (EHR) have become valuable for enhancing medical
decision making, as well as online disease detection and monitoring. Meanwhile, deep …
decision making, as well as online disease detection and monitoring. Meanwhile, deep …
Enhancing personalized healthcare via capturing disease severity, interaction, and progression
Personalized diagnosis prediction based on electronic health records (EHR) of patients is a
promising yet challenging task for AI in healthcare. Existing studies typically ignore the …
promising yet challenging task for AI in healthcare. Existing studies typically ignore the …
DP-MHAN: A Disease Prediction Method Based on Metapath Aggregated Heterogeneous Graph Attention Networks
Disease prediction as an important component of medical assistant diagnostic systems has
received much attention from researchers. Many studies attempt to extract disease-related …
received much attention from researchers. Many studies attempt to extract disease-related …
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 …
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 …
[图书][B] Deep Learning Predictive Modelling for Electronic Health Records
M Gupta - 2023 - search.proquest.com
With the digitization of health records over the last two decades there is a large amount of
health records data collected electronically. This data provides unprecedented research …
health records data collected electronically. This data provides unprecedented research …