AI-Enabled Algorithm for Automatic Classification of Sleep Disorders Based on Single-Lead Electrocardiogram
Healthy sleep is an essential physiological process for every individual to live a healthy life. Many sleep disorders both destroy the quality and decrease the duration of sleep. Thus, a convenient and accurate detection or classification method is important for screening and identifying sleep disor...
Guardado en:
Autores principales: | Erdenebayar Urtnasan, Eun Yeon Joo, Kyu Hee Lee |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/849e65508a0648e5b228863761527532 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
A Lightweight CNN Architecture for Automatic Modulation Classification
por: Zhongyong Wang, et al.
Publicado: (2021) -
Automatic Multi-Label ECG Classification with Category Imbalance and Cost-Sensitive Thresholding
por: Yang Liu, et al.
Publicado: (2021) -
Automatic Detection and Classification of Cough Events Based on Deep Learning
por: Hossein Tabatabaei Seyed Amir, et al.
Publicado: (2020) -
Review of Image Classification Algorithms Based on Convolutional Neural Networks
por: Leiyu Chen, et al.
Publicado: (2021) -
Automated Classification Model With OTSU and CNN Method for Premature Ventricular Contraction Detection
por: Liang-Hung Wang, et al.
Publicado: (2021)