Providing a fascinating glimpse into the future of health diagnostics, researchers from the National Heart and Lung Institute at Imperial College in London have developed an artificial intelligence (AI) model capable of predicting high blood pressure and associated complications using electrocardiogram (ECG) data. By analyzing large datasets of over one million ECGs, the AI system identifies subtle patterns in heart signals, allowing it to accurately assess a patient’s risk of developing hypertension, strokes, or heart attacks. The team believes this innovation could enable earlier interventions, such as lifestyle changes, potentially preventing severe outcomes and improving patient care.
The study, published in the JAMA Cardiology journal, showed that patients classified by the AI as high-risk were up to four times more likely to develop high blood pressure than those in lower-risk groups. Additionally, the AI tool was able to accurately predict complications, including strokes and heart attacks, independent of other clinical risk factors. Researchers aim to test the system in clinical trials starting later this year. Meantime, the team has developed similar models to predict other health risks, such as diabetes.
To check out Dr. Rath’s Cellular Health recommendations for the prevention and control of high blood pressure, see this page on our website.
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January 24, 2025AI Model Can Predict High Blood Pressure and Related Complications from ECGs
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A new artificial intelligence (AI) model can predict the risk of high blood pressure and potential complications using an electrocardiogram (ECG).
[Source: imperial.ac.uk]
[Image source: Adobe Stock]
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Providing a fascinating glimpse into the future of health diagnostics, researchers from the National Heart and Lung Institute at Imperial College in London have developed an artificial intelligence (AI) model capable of predicting high blood pressure and associated complications using electrocardiogram (ECG) data. By analyzing large datasets of over one million ECGs, the AI system identifies subtle patterns in heart signals, allowing it to accurately assess a patient’s risk of developing hypertension, strokes, or heart attacks. The team believes this innovation could enable earlier interventions, such as lifestyle changes, potentially preventing severe outcomes and improving patient care.
The study, published in the JAMA Cardiology journal, showed that patients classified by the AI as high-risk were up to four times more likely to develop high blood pressure than those in lower-risk groups. Additionally, the AI tool was able to accurately predict complications, including strokes and heart attacks, independent of other clinical risk factors. Researchers aim to test the system in clinical trials starting later this year. Meantime, the team has developed similar models to predict other health risks, such as diabetes.
To check out Dr. Rath’s Cellular Health recommendations for the prevention and control of high blood pressure, see this page on our website.
Dr. Rath Health Foundation
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