Diagnosis of Obstructive Sleep Apnea Using Feature Selection, Classification Methods, and Data Grouping Based Age, Sex, and Race

Diagnosis of Obstructive Sleep Apnea Using Feature Selection, Classification Methods, and Data Grouping Based Age, Sex, and Race

Obstructive sleep apnea (OSA) is a prevalent sleep disorder that affects approximately 3–7% of males and 2–5% of females. In the United States alone, 50–70 million adults suffer from various sleep disorders. OSA is characterized by recurrent episodes of breathing cessation during sleep, thereby lead...

Full description

Bibliographic Details
Main Authors: Alaa Sheta, Thaer Thaher, Salim R. Surani, Hamza Turabieh, Malik Braik, Jingwei Too, Noor Abu-El-Rub, Majdi Mafarjah, Hamouda Chantar, Shyam Subramanian
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Diagnostics
Subjects:
obstructive sleep apnea
grouping
feature selection
machine learning
Online Access:https://www.mdpi.com/2075-4418/13/14/2417

Internet

https://www.mdpi.com/2075-4418/13/14/2417

Similar Items