Medical Concept Representation Learning from Electronic Health Records and its Application on Heart Failure Prediction

Understand

Objective: To transform heterogeneous clinical data from electronic health records into clinically meaningful constructed features using data driven method that rely, in part, on temporal relations among data.

• Materials and Methods: The clinically meaningful representations of medical concepts and patients are the key for health analytic applications.
• Most of existing approaches directly construct features mapped to raw data (e.g., ICD or CPT codes), or utilize some ontology mapping such as SNOMED codes.
• However, none of the existing approaches leverage EHR data directly for learning such concept representation.