Improving Sleep Disorder Diagnosis Through Optimized Machine Learning Approaches

Improving Sleep Disorder Diagnosis Through Optimized Machine Learning Approaches

Classifying sleep disorders, such as obstructive sleep apnea and insomnia, is crucial for improving human quality of life due to their significant impact on health. The traditional expert-based classification of sleep stages, particularly through visual inspection, is challenging and prone to errors...

Full description

Saved in:
Bibliographic Details
Main Authors: Md. Atiqur Rahman, Israt Jahan, Maheen Islam, Taskeed Jabid, Md Sawkat Ali, Mohammad Rifat Ahmmad Rashid, Mohammad Manzurul Islam, Md. Hasanul Ferdaus, Md Mostofa Kamal Rasel, Mahmuda Rawnak Jahan, Shayla Sharmin, Tanzina Afroz Rimi, Atia Sanjida Talukder, Md. Mafiul Hasan Matin, M. Ameer Ali
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
SMOTEENN
ANOVA test
feature engineering
classification
sleep disorder
machine learning classifiers
Online Access:https://ieeexplore.ieee.org/document/10856004/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/10856004/

Similar Items