Sleep-based method forecasts heart issues a decade early
The study demonstrates that artificial intelligence technology can analyze electrical heart activity during sleep to predict the risks of cardiovascular diseases and mortality over the next ten years. Using electrocardiogram data recorded during sleep assessments, participants were classified according to their heart risk levels. The results showed that a higher risk level significantly increases the likelihood of developing heart disorders such as atrial fibrillation, stroke, and heart failure, as well as increasing the probability of death by between 65% and 82%. The adoption of this model has improved the accuracy of predicting cardiac complications compared to traditional factors, with the potential to be integrated into routine sleep examinations in the future for early diagnosis and better risk management.
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