Description: With all the attention focusing on open source chatGPT these days (a popular interactive form of artificial intelligence, or AI), it seems necessary to discuss how aspects of AI—especially machine learning—impact our work in sleep technology. Specifically, new research has set out to find new, more efficient and accurate ways to identify patients with sleep apnea, determine its severity, and even decide on more personalized treatment pathways. This month’s Journal Club address AI and OSA by first examining just what machine learning is, then exploring the history of AI in the healthcare industry, looking even more closely at how it has served the field of sleep medicine and technology. Then we’ll review the Maniaci, et al (2023) study, which takes a closer look at how certain algorithms might help sleep medicine practitioners to better help identify and treat those patients with more severe sleep breathing disorders.
CEC Credit(s): 1.0
Target Audience: Sleep technologists
Category: Journal Club
Free for members! $30 for all non-members.