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 …
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 …
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 …
Temporal-spatial Correlation Attention Network for Clinical Data Analysis in Intensive Care Unit
Recent advancements in medical information technology have enabled electronic health
records (EHRs) to store comprehensive clinical data which has ushered healthcare into the …
records (EHRs) to store comprehensive clinical data which has ushered healthcare into the …
[HTML][HTML] 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 …
Hitanet: Hierarchical time-aware attention networks for risk prediction on electronic health records
Deep learning methods especially recurrent neural network based models have
demonstrated early success in disease risk prediction on longitudinal patient data. Existing …
demonstrated early success in disease risk prediction on longitudinal patient data. Existing …
Collaborative graph learning with auxiliary text for temporal event prediction in healthcare
Accurate and explainable health event predictions are becoming crucial for healthcare
providers to develop care plans for patients. The availability of electronic health records …
providers to develop care plans for patients. The availability of electronic health records …
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 …
Domain knowledge guided deep learning with electronic health records
C Yin, R Zhao, B Qian, X Lv… - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
Due to their promising performance in clinical risk prediction with Electronic Health Records
(EHRs), deep learning methods have attracted significant interest from healthcare …
(EHRs), deep learning methods have attracted significant interest from healthcare …
BiteNet: bidirectional temporal encoder network to predict medical outcomes
Electronic health records (EHRs) are longitudinal records of a patient's interactions with
healthcare systems. A patient's EHR data is organized as a three-level hierarchy from top to …
healthcare systems. A patient's EHR data is organized as a three-level hierarchy from top to …