Mayo Clinic recently published a report highlighting the potential of artificial intelligence in predicting coronary disease diagnoses at an earlier stage when combined with echocardiograms.
According to a news release from Mayo Clinic, atherosclerotic cardiovascular disease, primarily driven by coronary artery disease, remains the leading cause of mortality worldwide. This condition involves the narrowing or blockage of arteries due to the accumulation of plaque.
New findings show that echocardiograms paired with artificial intelligence (ECG-AI), can identify warning signs and symptoms years earlier than ECG’s alone. ECG’s are a simple and widely available test to measure the heart's electrical activity, and AI can be trained to analyze those electrical signals to find hidden patterns that identify risks of disease, according to the Mayo Clinic press release.
Mayo Clinic, in partnership with Anumana, developed three varieties of ECG-AI. One variant was trained to detect coronary artery calcium, another was trained to detect coronary artery blockages, and the third was trained to spot impaired movement in segments within the left ventricle, which can be a sign of a previous heart attack.
"Used together, the three independent ECG-AI models predicted which patients had a high risk of hidden coronary artery disease and therefore a high risk of having a heart attack," Dr. Francisco Lopez-Jimenez, Mayo Clinic cardiologist and senior author of the paper, said, according to the news release. "This is important information to guide our conversations with patients at the point of care, especially since the AI was useful in calculating these risks for as short as three years. The addition of ECG-AI to see hidden risks sooner has the potential to save more lives. This model may also help identify people who do not know they have coronary disease who may benefit from lifesaving therapies.
This technology has been licensed to Anumana and Mayo Clinic is actively considering the financial benefits of commercializing this technology.
