Heterogeneous graph construction and HinSAGE learning from electronic medical records.Graph representation learning is a method for introducing how to effectively construct and learn patient embeddings using electronic medical records.  This study aims to address the challenge of implementing a complex and highly heterogeneous dataset, including the following: (1) demonstrating how to build a multi-attributed and multi-relational graph model (2) and applying a downstream disease prediction task of a patient's prognosis using the HinSAGE algorithm.  Moreover, we demonstrate an alternative bipartite model where we apply the model to the HinSAGE to perform the link prediction task for predicting the event occurrence.  Overall, our graph database successfully demonstrated efficient real-time query performance and showed HinSAGE implementation to predict cardiovascular disease event outcomes on supervised link prediction learning.
HinSAGE
This study aims to address the challenge of implementing a complex and highly heterogeneous dataset, including the following: (1) demonstrating how to build a multi-attributed and multi-relational graph model (2) and applying a downstream disease prediction task of a patient's prognosis using the HinSAGE algorithm. 
HinSAGE algorithm
Heterogeneous graph construction and HinSAGE learning from electronic medical records.Graph representation learning is a method for introducing how to effectively construct and learn patient embeddings using electronic medical records. 
graph representation learning
Heterogeneous graph construction and HinSAGE learning from electronic medical records.Graph representation learning is a method for introducing how to effectively construct and learn patient embeddings using electronic medical records. 
electronic medical records
We present a bipartite graph schema and a graph database construction in detail. 
graph database construction
The first constructed graph database illustrates a query of a predictive network that provides analytical insights using a graph representation of a patient's journey. 
graph representation of a patient's journey