ML Improves Mortality Prediction in STEMI for Asian Women
ML Improves Mortality Prediction in STEMI for Asian Women
Ensemble Machine Learning for Predicting In-Hospital Mortality in Asian Women with ST-Elevation Myocardial Infarction (STEMI)
Tags: Universiti Malaya, Malaysia, Computing Technology, Healthcare & Lifesciences
This study develops ensemble machine learning (ML) models to predict in-hospital mortality in Asian women with ST-elevation myocardial infarction (STEMI), a demographic often underrepresented in existing models. By analyzing data from the Malaysian National Cardiovascular Disease Database, the models identified key predictors such as systolic blood pressure, Killip class, and beta-blockers. The women-specific ML models outperformed the traditional TIMI Risk score and even non-gender-specific STEMI models. Applications include improving clinical decision-making for STEMI patients. The study underscores the importance of personalized care based on demographic-specific predictors.
IP Type or Form Factor: Discovery & Research; Software & Algorithm
TRL: 4 - minimum viable product built in lab
Industry or Tech Area: Big Data Analytics & Simulations; Healthcare Provider
