Multiple Graph Kernel Fusion Prediction of Drug Prescription

We present an end-to-end interpretable deep architecture that predicts the success of drug prescription based on multiple graph kernel fusion using a graphical representation of electronic health records. We formulate the predictive model as a binary graph classification problem with a set of graph kernels proposed to capture different aspects of graph structures through deep neural networks. Results using the Taiwanese National Health Insurance...