USA — A new study from Rutgers suggests that artificial intelligence (AI) may be able to predict cardiovascular diseases, such as atrial fibrillation and heart failure, by analyzing patients’ DNA.

Zeeshan Ahmed, a core faculty member at the Rutgers Institute for Health, Health Care Policy and Aging Research (IFH) and the lead author of the study, stated that “With the successful execution of our model, we predicted the association of highly significant cardiovascular disease genes tied to demographic variables like race, gender, and age.

However, the World Health Organization also estimated that over 75 percent of premature cardiovascular disease is preventable, according to the Rutgers study published in Genomics.

Despite significant advancements in cardiovascular disease diagnosis, prevention, and treatment, about half of the affected patients reportedly die within five years of receiving a diagnosis due to genetic and environmental factors.

Researchers said the use of AI and machine learning can accelerate the identification of genes that have important implications for cardiovascular disease, which can lead to improvements in diagnoses and treatment.

Machine learning is a type of artificial intelligence that helps computers learn how to solve problems on their own.

In the field of cardiovascular medicine, machine learning can be used to analyze data, like medical images or text, and make predictions about outcomes, like whether a patient will have a positive or negative response to treatment.

It does this by using mathematical equations and statistical analysis to find patterns in the data.

The study analyzed healthy patients and those diagnosed with cardiovascular disease and used AI and machine-learning models to investigate genes associated with the most common cardiovascular diseases, including atrial fibrillation and heart failure.

They identified a group of genes that were significantly associated with cardiovascular disease and found significant differences among race, gender, and age factors based on cardiovascular disease.

While age and gender factors correlated to heart failure, age and race factors correlated to atrial fibrillation. Scientists use artificial intelligence to detect heart disease.

For example, in the patients examined, the older the patient, the more likely they were to have cardiovascular disease.

The researchers suggest that timely understanding and precise treatment of cardiovascular disease will ultimately benefit millions of individuals by reducing the high risk for mortality and improving the quality of life.

They recommend future research to analyze the full set of genes in patients with cardiovascular disease to reveal important biomarkers and risk factors associated with cardiovascular disease susceptibility.

Artificial intelligence (AI) is gaining more attention in the field of cardiovascular treatment, as and Bristol Myers Squibb have announced a multi-year agreement to use AI-powered disease detection and care coordination.

They will deploy an AI algorithm and provider workflow software called Viz HCM, which is designed to identify and triage patients who may need further evaluation for the detection of hypertrophic cardiomyopathy (HCM).

HCM is a common inherited heart disease that affects around 750,000 people in the United States and 20 million people worldwide.

Using AI to detect HCM earlier can help doctors diagnose and treat patients before they develop more severe symptoms. has submitted a request to the FDA to approve the algorithm as a Software-as-a-Medical-Device, which is currently under review.

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