Artificial Intelligence Could Help Detect Onset of Cardiovascular Disease

A.I. could reduce costs and detect Heart Disease earlier.

A scan of the eye. Credit: UK Biobank

They says the human eyes are the window to the soul. They might also be the oracle of cardiovascular health, thanks to A.I.

Deep learning is a complex series of algorithms that enable computers to identify patterns in data and to make predictions.

Impact of A.I. on Cardiovascular Health

We always had a hunch this was coming but in January, 2022 for the first time, researchers at the University of Utah (U of U) Health have demonstrated that artificial intelligence (AI) could help predict the onset and course of cardiovascular disease.

We know that A.I. is making significant advances across healthcare, both for doctors and patients and healthcare systems as a whole. Early detection for cardiovascular issues is key.

Their findings are published in the journal PLOS Digital Health in a paper titled, “An explainable artificial intelligence approach for predicting cardiovascular outcomes using electronic health records.” The researchers collaborated with physicians from Intermountain Primary Children’s Hospital.

Using explainable Artificial Intelligence (AI) methodologies, the team then teased apart the intertwined, conditionally-dependent impacts of comorbid conditions and demography upon cardiovascular health, focusing on the key areas of heart transplant, sinoatrial node dysfunction and various forms of congenital heart disease.

Deep Learning to Read Retinal Scans

A separate study reveals more along these lines. In the research, led by the University of Leeds, deep learning techniques were used to train the AI system to automatically read retinal scans and identify those people who, over the following year, were likely to have a heart attack.  

• Doctors have recognized that changes to the tiny blood vessels in the retina are indicators of broader vascular disease, including problems with the heart.

• Writing in the journal Nature Machine Intelligence, the researchers report that the AI system had an accuracy of between 70% and 80% and could be used as a second referral mechanism for in-depth cardiovascular investigation.

I think both of these studies in January, 2022 paint a good pictures of how A.I. will used in screening for heart problems.

The use of deep learning in the analysis of retinal scans could revolutionize the way patients are regularly screened for signs of heart disease.

Professor Alex Frangi, who holds the Diamond Jubilee Chair in Computational Medicine at the University of Leeds and is a Turing Fellow at the Alan Turing Institute, supervised the research.

He said: "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.

Lowering the Cost of Healthcare

This is yet another example of how A.I. in healthcare could also lower costs.

This technique opens-up the possibility of revolutionizing the screening of cardiac disease. Retinal scans are comparatively cheap and routinely used in many optician practices. As a result of automated screening, patients who are at high risk of becoming ill could be referred to specialist cardiac services.

A.I. Studies have Gone Global in Democratization of A.I.’s Benefits

The study also demonstrates how democratized and global A.I. research is becoming.

The study involved a worldwide collaboration of scientists, engineers and clinicians from the University of Leeds; Leeds Teaching Hospitals' NHS Trust; the University of York; the Cixi Institute of Biomedical Imaging in Ningbo, part of the Chinese Academy of Sciences; the University of Cote d'Azur, France; the National Centre for Biotechnology Information and the National Eye Institute, both part of the National Institutes for Health in the US; and KU Leuven in Belgium.

The UK Biobank provided data for the study.

The AI system has the potential to identify individuals attending routine eye screening who are at higher future risk of cardiovascular disease, whereby preventative treatments could be started earlier to prevent premature cardiovascular disease."

Chris Gale, Professor of Cardiovascular Medicine, University of Leeds

Summary

• In the research, led by the University of Leeds, deep learning techniques were used to train an AI system to automatically read retinal scans and identify those people who, over the following year, were likely to have a heart attack.  

To read the blog at Leeds itself go here.

• This technique opens-up the possibility of revolutionizing the screening of cardiac disease, leading to earlier detection of heart disease.

If you enjoyed this article, you might enjoy another Newsletter I write at the intersection of Business and Technology.

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