Mayo Clinic doctors have developed an Artificial Intelligence (AI) algorithm that can use ECG to detect plaques on the walls of blood vessels. The study, which will enable early diagnosis of coronary heart disease and prevention of heart attacks, was published in the journal eClinicalMedicine.
Atherosclerosis, the buildup of fatty plaques on the walls of blood vessels, leads to narrowing or complete blockage of arteries. This significantly increases the risk of stroke and heart attack. Additionally, interruption of oxygen supply to the heart can lead to coronary heart disease. It often does not manifest itself, and the first sign of the disease may be sudden death or heart attack.
In a new study, scientists tested a new ECG-AI tool to detect coronary heart disease at an early stage. To develop it, they used health data from more than seven million patients in the United States. Three algorithms are aimed at detecting calcium deposits in the coronary artery, arterial occlusions and impaired mobility of the left ventricular segments of the heart. The last sign may indicate a heart attack.
Used together, three independent ECG-AI models predicted which patients were at high risk for silent coronary artery disease and therefore at increased risk of heart attack. These people may need to be more careful in preventing heart attack, and some may need medication.
An ECG is a widely available test that measures the electrical activity of the heart and does not require much time or money. Scientists believe that using ECG-AI in conjunction with standard prognostic tools will help save more lives.
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