The team that developed this is composed of clinical cardiologists, bioinformatics scientists, and PhD researchers from other fields. They are committed to researching the use of registry data to predict mortality and cardiac events in heart disease patients. In addition, we used air quality data in conjunction with cardiac factors to predict hospital admissions and cardiac deaths.
We hope with this unique calculator, we can help prevent avoidable deaths in the Malaysian population with heart attacks.

In the past 50 years, Malaysia has undergone a rapid evolution in terms of health and disease. Communicable diseases are no longer the leading cause of death, with heart disease taking the top spot for the past decade.
 
Unstable Angina (UA), Non-ST-Elevation Myocardial Infarction (NSTEMI), and ST-elevation Myocardial Infarction (STEMI) are the three types of heart attacks. STEMI patients have the highest mortality risk among these individuals. Nevertheless, current prediction tools are based on Western populations and may not fully reflect the Malaysian population’s specific risk variables.
 
However, the existing predictive tools, primarily based on Western populations, may overlook the unique risk variables present within our Malaysian community. That’s why our team has developed a region specific machine learning cardiovascular calculator. This tool accurately predicts ACS Risk and Mortality, leaning on insights from the NCVD cohort, along with Cardiovascular Risk Diseases (CVD) based on the REDISCOVER cohort while using a recent dataset from 2019. Uniquely, we have incorporated air quality factors into our risk model, offering a comprehensive understanding of environmental impact on cardiovascular health in Malaysia. With this novel step, we can give a more complete picture of the factors that affect cardiovascular health in Malaysia.