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Journal Club #83: AI and OSA

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.

Recorded: 4/27/2023

CEC Credit(s): 1.0

Target Audience: Sleep technologists

Length: 1-hour

Key:

Complete
Failed
Available
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Introduction
Open to view video.
Open to view video.
Part 1
Open to view video.
Open to view video.
Part 1 Quiz
4 Questions  |  Unlimited attempts  |  0/6 points to pass
4 Questions  |  Unlimited attempts  |  0/6 points to pass
Part 2
Open to view video.
Open to view video.
Part 2 Quiz
4 Questions  |  Unlimited attempts  |  0/11 points to pass
4 Questions  |  Unlimited attempts  |  0/11 points to pass
Part 3
Open to view video.
Open to view video.
Part 3 Quiz
3 Questions  |  Unlimited attempts  |  0/3 points to pass
3 Questions  |  Unlimited attempts  |  0/3 points to pass
Outro
Open to view video.
Open to view video.
Citations
Open to view video.
Open to view video.
Definitions
Review the key terms in this course.
Certificate
1.0 CEC credit  |  Certificate available
1.0 CEC credit  |  Certificate available