Graph-based Fusion Modeling and Explanation forDisease Trajectory Prediction
Description
We propose a relational graph to incorporate clinical similarity between patients while building personalized clinical event predictors with a focus on hospitalized COVID-19 patients. Our graph formation process fuses heterogeneous data, i.e., chest
