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I met the same problem when I was doing the experiment referring to the repo you mentioned, so I only reported the result from the code. I also notice "shallow" method in the table above has a closer result in terms of scale, but I don't really know the reason for the gap.
In your paper, the result of the readmission task based on eICU dataset is 0.3986. GCT's AUPRC is 0.3794.
But in GCT paper (Learning the Graphical Structure of Electronic Health Records with
Graph Convolutional Transformer), the result of the readmission task based on eICU dataset is 0.5313.
What makes such a difference?
I ran both codes from your repo and theirs. I found out that the results were close to yours.
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