Mount Sinai researchers are developing and studying models powered by artificial intelligence (AI) to identify the risk of cardiovascular disease events in patients with obstructive sleep apnea. The prediction models, using machine-learning techniques, will also help classify patients who may benefit from the most common treatment option for the disorder.
The researchers said their personalized tools will provide a novel approach to enhancing management of obstructive sleep apnea by optimizing the best decisions for treatment plans and improving cardiovascular outcomes. The study is supported by a four-year, $3 million grant from the National Heart, Lung, and Blood Institute of the National Institutes of Health (NIH).
Obstructive sleep apnea is a serious and chronic condition in which the upper airway becomes blocked, leading to brief pauses in breathing during sleep. It affects more than 1 billion people worldwide. The most common treatment for obstructive sleep apnea is use of a breathing device called a continuous positive airway pressure (CPAP) machine, which provides air pressure throughout the upper airway to keep it open and help with breathing while asleep. Previous studies have established the prevalence of obstructive sleep apnea and its association to cardiovascular disease. However, little research has demonstrated the benefits of continuous CPAP use on the rate of cardiovascular events.
