According to new research out of Rutgers University, artificial intelligence (AI) has the potential to alter how we anticipate and prevent cardiovascular disease dramatically. Atrial fibrillation and heart failure, which account for 45% of all fatalities attributable to cardiovascular disease, can be predicted by AI algorithms studying a patient’s DNA.
Using AI to find genes associated with cardiovascular disease faster could improve diagnosis and therapy, according to the study. Furthermore, it has the potential to avert 75 percent of early cardiovascular diseases due to their effects on both genetics and the environment.
The researchers in this study hoped that by using AI and ML techniques, they could help advance precision medicine for cardiovascular diseases. Sample collection, data generation by sequencing, data processing via bioinformatics, and prediction analysis using artificial intelligence and machine learning make up the three main phases of the study as a whole.
Rutgers IFH core faculty member and lead author Zeeshan Ahmed said their model accurately predicted the correlation of very significant cardiovascular disease genes linked to demographic characteristics like race, gender, and age.
Age and gender characteristics were associated with heart failure, and age and race factors were associated with atrial fibrillation, but the study also identified substantial differences based on race. Researchers believe that by studying the complete genomes of people with cardiovascular illness, they can identify critical biomarkers and risk factors linked to the development of cardiovascular disease.
The United States and the rest of the world have a disproportionately high cardiovascular disease (CVD) death rate. Myocardial infarction and congenital heart disease are both examples of this cluster of diseases that tend to run in families.
More tailored treatments based on predictive analysis and deep phenotyping will be possible thanks to new insights into cardiovascular disease (CVD) made possible by the appropriate use of artificial intelligence (AI) and machine learning (ML) technologies.
The purpose of this research was to aid doctors in the early diagnosis and prevention of cardiovascular disease by identifying genetic biomarkers linked with CVD susceptibility and predicting CVD with a high degree of accuracy.
In the long run, millions of people could gain from artificial intelligence being used to anticipate and treat cardiovascular disease, lowering their chance of death and increasing their quality of life.