AI can spot an irregular heartbeat that doctor’s can’t
AI can spot an irregular heartbeat from just a 10-second scan by looking for tiny signals that may be ‘invisible to the human eye’
- Researchers used the AI test against ECGs that had already been taken
- The test accurately spotted atrial fibrillation 83% of the time overall
- Many people go undiagnosed because their heart rate is not always abnormal
- AI takes seconds to spot signs, compared to current tests which can take years
Artificial intelligence can spot an irregular heartbeat from a scan which may appear normal to doctors, scientists claim.
The test was able to identify abnormalities in just 10 seconds, compared to current tests which can take weeks or years to interpret.
Doctors said the AI system, which uses deep learning, can find signals in heart tests that may be ‘invisible to the human eye’.
Researchers at the The Mayo Clinic in Rochester, Minnesota, trained an AI model to detect the signature of atrial fibrillation rhythm, and then put it to test.
The test was able to accurately spot the unusual heart rhythm 83 per cent of the time, according to a study.
Atrial fibrillation, which raises the risk of stroke and heart failure, often goes undetected because patients’ hearts go in and out of the abnormal rhythm.
AI can spot an irregular heartbeat from a ten second scan compared to current tests that can take years to diagnose atrial fibrillation (stock image)
The study, published in The Lancet, involved data from almost 181,000 patients who were already being investigated for having an abnormal heart rhythm.
Around 650,000 ECG scans were taken from the period between 1993 and 2017 in the study.
During an ECG, small stickers called electrodes are attached to the arms, legs and chest, and connected by wires to an ECG machine.
Every time the heart beats, it produces tiny electrical signals. An ECG machine traces these signals onto paper, which is read by a doctor.
The data was divided into patients who had tested either positive or negative for AF.
When the AI was tested on the first ECG from each patient, it accurately spotted the presence, history or impending AF 79 per cent of the time.
When using multiple ECGs for the same patient, the accuracy improved to 83 per cent.
Dr Paul Friedman, chair of the department of cardiovascular medicine at The Mayo Clinic, said: ‘Applying an AI model to the ECG permits detection of atrial fibrillation even if not present at the time the ECG is recorded.
‘It is like looking at the ocean now and being able to tell that there were big waves yesterday.’
Writing in the journal, they said: ‘We used an AI model to find signals in the ECG that might be invisible to the human eye but contain important information about the presence of atrial fibrillation.’
The study is the first to use deep learning, which is a form of AI in which the system is able to improve each time it repeats the same task by learning from its past mistakes.
Since the AI is only as good as the data it is trained against, in this case using ECGs from people already being investigated, there could be mistakes in the interpretation when the test is used on the general population.
It also did not test on people with unexplained stroke.
‘However, the ability to test quickly and inexpensively with a non-invasive and widely available test might one day help identify undiagnosed atrial fibrillation and guide important treatment, preventing stroke and other serious illness,’ Dr Friedmen said.
After an unexplained stroke, it is important to accurately detect AF so that patients with it are given treatment.
WHAT IS DEEP LEARNING?
Deep learning is a form of machine learning concerned with algorithms which have a wide range of applications.
It is a field which was inspired by the human brain and focuses on building artificial neural networks.
It was formed originally based on brain simulations and to allow learning algorithms to become better and easier to use.
Processing vast amounts of complex data then becomes much easier and allows researchers to trust algorithms to draw accurate conclusions based on the parameters the researchers have set.
Task-specific algorithms which exist are better for specific tasks and goals but deep-learning allows for a wider scope of data collection.
Currently, a large and sometimes uncomfortable device will monitor their heart for weeks or even years, in which time they could have another stroke.
The researchers also speculate that AI may one day be used by doctors to screen high-risk groups.
Screening people with hypertension, diabetes, or age over 65 years for AF could help avoid further problems.
Dr Xiaoxi Yao, a study co-investigator from The Mayo Clinic, said: ‘It is possible that our algorithm could be used on low-cost, widely available technologies, including smartphones.
‘However, this will require more research before widespread application.’
The authors note several limitations, particularly that the study participants may have had a higher prevalence of AF compared to the general population.
Dr Malcolm Finlay, consultant cardiologist in Barts Heart Centre in London, said: ‘This really limits the applicability of the findings to real world situations, where we would like to use ECGs to determine which patients will benefit from certain treatment for AF to decrease their risks of having a stroke.’
Professor Kazem Rahimi, deputy director at The George lnstitute for Global Health, University of Oxford said: ‘This is a great study which could certainly change the way we screen for patients with AF.
‘The results are quite striking. However, the findings do need further validation in the general population and over a long time period to monitor for any mistakes the algorithm may make.’
WHAT IS ATRIAL FIBRILLATION?
Atrial fibrillation is a heart condition that causes an irregular and often abnormally fast heart rate.
A normal heart rate should be regular and between 60 and 100 beats a minute when you’re resting.
You can measure your heart rate by feeling the pulse in your neck or wrist.
In atrial fibrillation, the heart rate is irregular and can sometimes be very fast. In some cases, it can be considerably higher than 100 beats a minute.
This can cause problems including dizziness, shortness of breath and tiredness.
Atrial fibrillation is the most common heart rhythm disturbance, affecting around 1 million people in the UK.
It can affect adults of any age, but it’s more common in older people. It affects about 7 in 100 people aged over 65.
You may be aware of noticeable heart palpitations, where your heart feels like it’s pounding, fluttering or beating irregularly, often for a few seconds or, in some cases, a few minutes.
You should make an appointment to see your GP if:
- you notice a sudden change in your heartbeat
- your heart rate is consistently lower than 60 or above 100 (particularly if you’re experiencing other symptoms of atrial fibrillation, such as dizziness and shortness of breath)
- See your GP as soon as possible if you have chest pain.
Source: NHS
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