An artificial intelligence model can diagnose obstructive sleep apnoea (OSA) with nearly 90 per cent accuracy using only a night-vision camera, potentially eliminating the need for invasive tests in specialized laboratories.
OSA occurs when the walls of the throat relax and narrow during sleep, which is associated with high blood pressure, type 2 diabetes, and heart disease. The current standard method for diagnosis is polysomnography (PSG), which requires an overnight stay in a hospital or sleep laboratory.