image: Diagnosing sleep apnea with machine learning. view more
Credit: ATS
ATS 2019, Dallas, TX -- Using machine learning to analyze jaw movements during sleep, doctors may be able to diagnose obstructive sleep apnea in patients with mild to severe OSA with an accuracy comparable to polysomnography, the gold standard for OSA diagnosis, according to research presented at ATS 2019. The researchers said this unique diagnostic method is promising because it provides information about respiratory effort during sleep, can be used at home and is cost effective.
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Session: D99 A Look to the Future of Sleep. Use of Novel Technologies and Software Analysis
Abstract Presentation Time: Wednesday, May 22, 1:45 p.m. CT
Location: Dallas Ballroom G (Level 3), Omni Dallas Downtown