ArticleScientific reports2026
Machine learning-based prediction of mortality risk from air pollution-induced acute coronary syndrome in the Western Pacific region.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Machine-learning-based cardiovascular mortality prediction using a cumulative PMScientific reports · 2026Observational
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11 authors.
Funding
Abstract
Air pollution is a growing cardiovascular risk in Southeast Asia, particularly in the Western Pacific region where transboundary haze and urban emissions are prevalent. Despite its relevance, traditional risk scores for Acute Coronary Syndrome (ACS) often overlook environmental factors. This study aims to assess the predictive value of air pollution exposure on ACS mortality using machine learning (ML) techniques, thereby addressing this clinical-environmental data gap. We combined clinical data from the National Cardiovascular Disease Database (NCVD) of Malaysia and daily air quality data (NOx, SO
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