Towards Validating the Effectiveness of Obstructive Sleep Apnea Classification from Electronic Health Records Using Machine Learning
Obstructive sleep apnea (OSA) is a common, chronic, sleep-related breathing disorder characterized by partial or complete airway obstruction in sleep. The gold standard diagnosis method is polysomnography, which estimates disease severity through the Apnea-Hypopnea Index (AHI). However, this is expe...
Main Authors: | Jayroop Ramesh, Niha Keeran, Assim Sagahyroon, Fadi Aloul |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-10-01
|
Series: | Healthcare |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-9032/9/11/1450 |
Similar Items
-
Obstructive Sleep Apnea and Hearing Loss: Is There Any Correlation?
by: Pankaj Chauhan, et al.
Published: (2023-07-01) -
The Usefulness of ApneaLink as a Screening Test for Diagnosis of Obstructive Sleep Apnea
by: Young Bin Yun, et al.
Published: (2022-09-01) -
Atypical Catathrenia Mimicking Sleep Choking Sound of Obstructive Sleep Apnea
by: Ki-Hwan Ji
Published: (2023-06-01) -
Sleep Apnea
by: Nazia Uzma, et al.
Published: (2017-07-01) -
Study of undiagnosed clinical hypothyroidism in patients with obstructive sleep apnea
by: Ayman Salem, et al.
Published: (2022-01-01)