Med-MGF: multi-level graph-based framework for handling medical data imbalance and representation.

ABSTRACT:

Background

Modeling patient data, particularly electronic health records (EHR), is one of the major focuses of machine learning studies in healthcare, as these records provide clinicians with valuable information that can potentially assist them in disease diagnosis and decision-making.

Methods

In this study, we present a multi-level graph-based framework called MedMGF, which models both patient medical profiles extracted from EHR data and their relationship network of health profiles in a single architecture. The medical profiles consist of several layers of data embedding derived from interval records obtained during hospitalization, and the patient-patient network is created by measuring the similarities between these profiles. We also propose a modification to the Focal

SUBMITTER: Nguyen TM 

PROVIDER: S-EPMC11367907 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature