Cargando…
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...
Autores principales: | Urtnasan, Erdenebayar, Joo, Eun Yeon, Lee, Kyu Hee |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8620146/ https://www.ncbi.nlm.nih.gov/pubmed/34829400 http://dx.doi.org/10.3390/diagnostics11112054 |
Ejemplares similares
-
Deep Convolutional Recurrent Model for Automatic Scoring Sleep Stages Based on Single-Lead ECG Signal
por: Urtnasan, Erdenebayar, et al.
Publicado: (2022) -
Deep Learning for Automatic Detection of Periodic Limb Movement Disorder Based on Electrocardiogram Signals
por: Urtnasan, Erdenebayar, et al.
Publicado: (2022) -
Automatic Prediction of Atrial Fibrillation Based on Convolutional Neural Network Using a Short-term Normal Electrocardiogram Signal
por: Erdenebayar, Urtnasan, et al.
Publicado: (2019) -
Noninvasive Screening Tool for Hyperkalemia Using a Single-Lead Electrocardiogram and Deep Learning: Development and Usability Study
por: Urtnasan, Erdenebayar, et al.
Publicado: (2022) -
Identification of Sleep Apnea Severity Based on Deep Learning from a Short-term Normal ECG
por: Urtnasan, Erdenebayar, et al.
Publicado: (2020)