Comorbidity network analysis using graphical models for electronic health records

ABSTRACT:

Importance

The comorbidity network represents multiple diseases and their relationships in a graph. Understanding comorbidity networks among critical care unit (CCU) patients can help doctors diagnose patients faster, minimize missed diagnoses, and potentially decrease morbidity and mortality.

Objective

The main objective of this study was to identify the comorbidity network among CCU patients using a novel application of a machine learning method (graphical modeling method). The second objective was to compare the machine learning method with a traditional pairwise method in simulation.

Method

This cross-sectional study used CCU patients' data from Medical Information Mart for the Intensive Care-3 (MIMIC-3) dataset, an electronic health record (EHR) of patients

SUBMITTER: Zhao B 

PROVIDER: S-EPMC10470017 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature