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Found 3 papers, 2 papers with code
Temporal Cascade and Structural Modelling of EHRs for Granular Readmission Prediction
Although a point process (e. g., Hawkes process) is able to model a cascade temporal relationship, it strongly relies on a prior generative process assumption.
$\mathtt{MedGraph:}$ Structural and Temporal Representation Learning of Electronic Medical Records
To address these limitations, we present $\mathtt{MedGraph}$, a supervised EMR embedding method that captures two types of information: (1) the visit-code associations in an attributed bipartite graph, and (2) the temporal sequencing of visits through a point process.
Gaussian Embedding of Large-scale Attributed Graphs
Graph embedding methods transform high-dimensional and complex graph contents into low-dimensional representations.
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