Predictive Modeling with Temporal Graphical Representation on Electronic Health Records.

ABSTRACT: Deep learning-based predictive models, leveraging Electronic Health Records (EHR), are receiving increasing attention in healthcare. An effective representation of a patient's EHR should hierarchically encompass both the temporal relationships between historical visits and medical events, and the inherent structural information within these elements. Existing patient representation methods can be roughly categorized into sequential representation and graphical representation. The sequential representation methods focus only on the temporal relationships among longitudinal visits. On the other hand, the graphical representation approaches, while adept at extracting the graph-structured relationships between various medical events, fall short in effectively integrate temporal information. To

SUBMITTER: Chen J 

PROVIDER: S-EPMC11446542 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature