Scientists may be able to predict cardiovascular disease in individuals by using artificial intelligence (AI) to look at genes in DNA, according to a new study. Atrial fibrillation and heart failure are examples of cardiovascular disease.
“The successful execution of our model predicted the association of highly significant cardiovascular disease genes associated with demographic variables such as race, gender and age.” Aging Research (IFH) ) and the first author of this study, published in Genomics.
According to the World Health Organization, cardiovascular disease is the leading cause of death worldwide, yet it is estimated that more than 75% of early cardiovascular disease is preventable. Atrial fibrillation and heart failure contribute to approximately 45% of all cardiovascular deaths.
Despite significant advances in diagnosing, preventing, and treating cardiovascular disease, it is reported that approximately half of those affected die within 5 years of diagnosis for a variety of reasons. Includes genetic and environmental factors. Researchers say the use of AI and machine learning could accelerate the ability to identify genes with important implications for cardiovascular disease, leading to improved diagnosis and treatment.
IFH researchers will analyze healthy patients and those diagnosed with cardiovascular disease and use AI and machine learning models to link them to the most common symptoms of cardiovascular disease, such as atrial fibrillation and heart failure. We investigated genes known to
They identified a group of genes significantly associated with cardiovascular disease. Researchers also found significant differences in factors such as race, gender and age based on cardiovascular disease. Age and gender factors correlated with heart failure, whereas age and race factors correlated with atrial fibrillation. For example, among the patients tested, the older the patient, the more likely they were to have cardiovascular disease.
Ahmed, an assistant professor of medicine at Rutgers Robert Wood Johnson School of Medicine, said: .
Future studies should extend this approach by analyzing the full set of genes in patients with cardiovascular disease, the researchers say. This may reveal important biomarkers and risk factors associated with cardiovascular disease susceptibility.
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