New AI Test Helps Doctors Diagnose Heart Attacks Faster

Researchers that have developed this AI tool are hoping that it would massively reduce unnecessary admissions into emergency units, while also saving lives through a timely diagnosis

Health and Artificial Intelligence experts have developed a new test that helps doctors diagnose heart attacks in a fast and accurate manner. Developers of the AI tool are hoping that it would go on to massively reduce unnecessary admissions into emergency units which are already quite busy and will also save lives through a timely diagnosis thus helping both heart patients and hospitals.

In order to test this new AI tool named the ‘CoDE-ACS’, researchers conducted a trial on over 10,286 people. It was found that the CoDE-ACS was able to rule out the possibility of a heart attack in twice as many patients, when compared to the testing methods being actively used.

It was reported that the CoDE-ACS had an accuracy of 99.6% making it the most precise detection tool for heart attacks.

The CoDE-ACS is currently under clinical testing in Scotland, receiving support from Wellcome Leap, an organization created to accelerate discovery and innovation in the health sector, who is analyzing whether the tool really does help reduce pressure on emergency departments inside crowded hospitals.

Heading this research, the professor of cardiology at the Centre for Cardiovascular Science, University of Edinburgh, Nicholas Mills said;

“For patients with acute chest pain due to a heart attack, early diagnosis and treatment saves lives. Unfortunately, many conditions cause these common symptoms, and the diagnosis is not always straightforward.”

“Harnessing data and artificial intelligence to support clinical decisions has enormous potential to improve care for patients and efficiency in our busy emergency departments,” he added.

The current gold standard for diagnosing a heart attack is through measuring the levels of protein troponin in the blood. The protein troponin method, however, is different for each person since results are affected by age, gender and other health conditions.

It’s reported that women who go through the protein troponin test are 50% more likely to be incorrectly diagnosed at first. This massively increases the levels of risk, since any incorrect diagnosis for a heart attack can increase the chances of death by 70%.

Developed and trained on the data of over 10,000 heart patients, the CoDE-ACS can prevent this since the tool uses multiple metrics such as age, gender, ECG test results, medical history and troponin levels, to predict whether a person has a heart attack.

“CoDE-ACS has the potential to rule-in or rule-out a heart attack more accurately than current approaches. It could be transformational for emergency departments, shortening the time needed to make a diagnosis, and much better for patients,” said MD of the British Heart Foundation, Professor Sir Nilesh Samani.

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