It would be a major breakthrough if something like the Apple Watch could detect it passively or help diagnose it, the report added.

The study included 2,454 patients from the US and 11 other countries.

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From August 2021 to February 2022, these participants sent over 1,25,000 ECGs via their Apple Watch.

These results were then "scrubbed and processed via a proprietary AI algorithm developed by the researchers", according to the report.

By using the mean prediction within a 30-day window or the closest ECG relative to the echocardiogram that determined the EF, the AI algorithm detected patients with a low EF (ejection fraction) with an area under the curve of 0.885 (95 per cent confidence interval 0.823-0.946) and 0.881 (0.815-0.947), said the report.

The findings showed that "consumer-watch ECGs acquired in nonclinical environments can identify patients with cardiac dysfunction".

The study also infers that "the potential of smartwatches to assist with conducting remote digital health studies is just in the beginning phases".

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