Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer

Understand

Effective modeling of electronic health records (EHR) is rapidly becoming an important topic in both academia and industry.

• A recent study showed that using the graphical structure underlying EHR data (e.g.
• relationship between diagnoses and treatments) improves the performance of prediction tasks such as heart failure prediction.
• However, EHR data do not always contain complete structure information.