AI helps detect atrial fibrillation cheaply and reliably
A startling new study from Mayo Clinic shows that artificial intelligence (AI) can help pick up the earliest signs of the potentially fatal irregularity in heart rhythm called atrial fibrillation (AF) on electrocardiography (EKG)– even when the heart rhythm is perfectly normal at the time of testing.

This means that AI can help the physician detect asymptomatic AF in the recent past, or warn of AF that is about to happen. In addition, this study improves the utility of EKG which is a very simple, inexpensive and widespread test used to look for heart disease related to many factors.

The current study used 450,000 EKGs carried out on Mayo Clinic patients, retrieved from the over 7 million stored in its digital archives, to train AI on the very slight alterations that show the heart structure is different from normal, due to AF. These are such small changes that only AI can possibly scrutinize the EKG with sufficient minuteness and accuracy to pick them up.

The next step was to test the trained AI on over 130,000 EKGs from 36,000 live patients. The tested EKGs all showed normal heart rhythm, but about 3,000 patients had a history of at least one AF episode. Astonishingly and gratifyingly, the AI was able to pick up 90% of AF-positive patients using these ‘normal’ EKGs, using the subtle alterations it had already learnt to recognize as characteristic of AF.

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