HealthGAT: Node Classifications in Electronic Health Records using Graph Attention Networks

arXiv:2403.18128v1 Announce Type: new
Abstract: While electronic health records (EHRs) are widely used across various applications in healthcare, most applications use the EHRs in their raw (tabular) format. Relying on raw or simple data pre-processing can greatly limit the performance or even applicability of downstream tasks using EHRs. To address this challenge, we present HealthGAT, a novel graph attention network framework that utilizes a hierarchical approach to generate embeddings from EHR, surpassing traditional graph-based methods. Our model iteratively refines the …

abstract applications arxiv attention cs.cy cs.lg data electronic electronic health records format graph health healthcare networks node performance pre-processing processing raw records simple tabular tasks type