Multi-Objective Hyperparameter Optimization of Convolutional Neural Network for Obstructive Sleep Apnea Detection

Multi-Objective Hyperparameter Optimization of Convolutional Neural Network for Obstructive Sleep Apnea Detection

Obstructive sleep apnea (OSA) is a common sleep disorder characterized by interrupted breathing during sleep. Because of the cost, complexity, and accessibility issue related to polysomnography, the gold standard test for apnea detection, automation of the diagnostic test based on a simpler method i...

Full description

Bibliographic Details
Main Authors: Sheikh Shanawaz Mostafa, Fabio Mendonca, Antonio G. Ravelo-Garcia, Gabriel Julia-Serda, Fernando Morgado-Dias
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Biomedical signal processing
CNN
genetic algorithms
machine intelligence
medical expert systems
Pareto optimization
Online Access:https://ieeexplore.ieee.org/document/9139951/

Internet

https://ieeexplore.ieee.org/document/9139951/

Similar Items