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AI can predict signs of a heart attack within a year -- from a routine eye test

#artificialintelligence

A team from the University of Leeds believes this AI tool opens the door to a cheap and simple screening program for the world's No. 1 killer. Their tests find the computer can predict patients at risk of a heart attack in the next 12 months with up to 80% accuracy. The breakthrough adds to evidence that our eyes are not just "windows to the soul," but windows to overall health as well. "Cardiovascular diseases, including heart attacks, are the leading cause of early death worldwide and the second-largest killer in the UK. This causes chronic ill-health and misery worldwide," project supervisor Professor Alex Frangi says in a university release.


AI can predict signs of a heart attack within a year -- from a routine eye test

#artificialintelligence

A team from the University of Leeds believes this AI tool opens the door to a cheap and simple screening program for the world's number one killer. Their tests find the computer can predict patients at risk of a heart attack in the next 12 months with up to 80 percent accuracy. The breakthrough adds to evidence that our eyes are not just "windows to the soul," but windows to overall health as well. "Cardiovascular diseases, including heart attacks, are the leading cause of early death worldwide and the second-largest killer in the UK. This causes chronic ill-health and misery worldwide," project supervisor Professor Alex Frangi says in a university release.


AI can predict signs of a heart attack within a year -- from a routine eye test

#artificialintelligence

An artificial intelligence system is capable of spotting whether someone will have a heart attack within the next year -- through a routine eye scan. A team from the University of Leeds believes this AI tool opens the door to a cheap and simple screening program for the world's number one killer. Their tests find the computer can predict patients at risk of a heart attack in the next 12 months with up to 80 percent accuracy. The breakthrough adds to evidence that our eyes are not just "windows to the soul," but windows to overall health as well. "Cardiovascular diseases, including heart attacks, are the leading cause of early death worldwide and the second-largest killer in the UK. This causes chronic ill-health and misery worldwide," project supervisor Professor Alex Frangi says in a university release.


Deep Learning Models Predict Cardiovascular Risk Factors from Images of the Eye

@machinelearnbot

The ability to stratify patients by cardiovascular risk is essential for identifying those likely to suffer a heart attack, stroke, or other heart disease in the future. High-risk patients can then take steps to improve their cardiovascular health. Doctors typically take into account a variety of risk factors: demographics such as age, sex and ethnicity; daily behaviors like exercise, smoking status and diet; as well as results from blood pressure and cholesterol tests. As a simple alternative to the traditional patient questionnaire and blood tests, a team of researchers from Google Research and the Stanford School of Medicine have developed deep learning models to predict cardiovascular risk factors from photographs of the back of the retina. Since these retinal fundus images are already collected for diabetic eye disease screening, this initial study suggests that deep learning could uncover additional information that could be further leveraged for preventative health.


Eye test uses AI to predict macular degeneration

Daily Mail - Science & tech

A new eye test that uses artificial intelligence AI to study retina scans can predict age-related macular degeneration (AMD) three years before symptoms start. The first part of the'pioneering' test, developed by researchers at University College London, is called DARC. DARC involves injecting dye into a person's bloodstream to illuminate'stressed' endothelial cells in the retina, so they appear bright white under a fluorescent camera. These'stressed' retinal cells could lead to abnormalities and later leaking blood vessels – causing AMD, which can severely compromise the central field of vision. The second part of the test uses an AI algorithm, trained to detect whether the highlighted white spots are around the macula – which indicates high AMD risk.