New AI Tool Predicts Fatal Heart Rhythm with 80% Accuracy

New AI Tool Predicts Fatal Heart Rhythm with 80% Accuracy

The likelihood of a fatal cardiac rhythm can now be predicted with 80% accuracy, according to a new artificial intelligence (AI) technology created by British researchers.

A disturbance in the heart’s rhythm that arises from the ventricles, the bottom chambers, is known as ventricular arrhythmia, or VA. Rapid heartbeats and falling blood pressure are the condition’s hallmarks. If treatment is delayed, these symptoms may worsen and result in an abrupt death.

A UK team led by the University of Leicester created the AI technology known as VA-ResNet-50. The Holter electrocardiograms (ECGs) of 270 persons obtained between 2014 and 2022 throughout their typical daily routine at home were examined using the technology in their study, which was published in the European Heart Journal: Digital Health.

Approximately 159 had died from fatal ventricular arrhythmias, with an average of 1.6 years after the ECG.

In order to determine whether a patient’s heart was capable of deadly arrhythmias, VA-ResNet-50 was retrospectively utilized to analyze “normal for patient” cardiac rhythms.

The AI technology successfully identified which patient’s heart was capable of ventricular arrhythmia on four out of five occasions.

According to Professor Andre Ng, the head of the department of cardiovascular sciences at the university and a professor of cardiac electrophysiology, “current clinical guidelines that help us to decide which patients are most at risk of going on to experience ventricular arrhythmia and who would most benefit from the life-saving treatment with an implantable cardioverter defibrillator are not accurate enough, leading to a significant number of deaths from the condition.”

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Crucially, the professor stated that “the risk of a lethal event was three times higher than that of normal adults if the tool said a person was at risk.”

“While normal cardiac rhythm offers a novel lens through which we can determine their risk and suggest appropriate treatment, ultimately saving lives,” the speaker continued, referring to the application of artificial intelligence in the analysis of patients’ ECGs.