Cargando…
A Deep Neural Network Ensemble Classifier with Focal Loss for Automatic Arrhythmia Classification
Automated electrocardiogram classification techniques play an important role in assisting physicians in diagnosing arrhythmia. Among these, the automatic classification of single-lead heartbeats has received wider attention due to the urgent need for portable ECG monitoring devices. Although many he...
Autores principales: | Wu, Han, Zhang, Senhao, Bao, Benkun, Li, Jiuqiang, Zhang, Yingying, Qiu, Donghai, Yang, Hongbo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9481402/ https://www.ncbi.nlm.nih.gov/pubmed/36118121 http://dx.doi.org/10.1155/2022/9370517 |
Ejemplares similares
-
Multifunctional Biosensing Platform Based on Nickel-Modified Laser-Induced Graphene
por: Tong, Yao, et al.
Publicado: (2023) -
Study on Flexible sEMG Acquisition System and Its Application in Muscle Strength Evaluation and Hand Rehabilitation
por: Liu, Chang, et al.
Publicado: (2022) -
Ensemble learning-based approach for automatic classification of termite mushrooms
por: Duong, Thi Kim Chi, et al.
Publicado: (2023) -
FLANNEL (Focal Loss bAsed Neural Network EnsembLe) for COVID-19 detection
por: Qiao, Zhi, et al.
Publicado: (2020) -
Cardiovascular and Diabetes Diseases Classification Using Ensemble Stacking Classifiers with SVM as a Meta Classifier
por: Khan, Asfandyar, et al.
Publicado: (2022)