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Graph-based Fusion Modeling and Explanation for Disease Trajectory Prediction
2022-10-28
health informatics
Title + abstract only
View on medRxiv
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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 X-rays as node features and non-imaging EHR for edge formation. While node represents a snap-shot in time for a single patient, weighted edge structure encodes complex clinical patterns among patients. While age and gender have been used in the past ...
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