Spatiotemporal associations between air pollution and emergency room visits for cardiovascular and cerebrovascular diseases in Korea using a multivariate graph autoencoder modeling approach: an ecological study.

ABSTRACT:

Purpose

This study aimed to assess the spatiotemporal associations between air pollution and emergency room visits for cardiovascular and cerebrovascular diseases in South Korea using a graph autoencoder (GAE). A multivariate graph-based approach was used to uncover seasonal and regional variations in pollutant-disease relationships.

Methods

We collected monthly data from 2022 to 2023, including concentrations of 6 air pollutants (SO2, NO2, O3, CO, PM10, and PM2.5) and emergency room visits for 4 disease types: cardiac arrest, myocardial infarction, ischemic stroke, and hemorrhagic stroke. Pearson correlation coefficients were used to construct adjacency matrices, which, along with normalized feature matrices, were used as inputs to the GAE. The model was trained separately

SUBMITTER: Wang S 

PROVIDER: S-EPMC12362291 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature