Cargando…
ECG Classification for Detecting ECG Arrhythmia Empowered with Deep Learning Approaches
According to the World Health Organization (WHO) report, heart disease is spreading throughout the world very rapidly and the situation is becoming alarming in people aged 40 or above (Xu, 2020). Different methods and procedures are adopted to detect and diagnose heart abnormalities. Data scientists...
Autores principales: | Rahman, Atta-ur, Asif, Rizwana Naz, Sultan, Kiran, Alsaif, Suleiman Ali, Abbas, Sagheer, Khan, Muhammad Adnan, Mosavi, Amir |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357747/ https://www.ncbi.nlm.nih.gov/pubmed/35958748 http://dx.doi.org/10.1155/2022/6852845 |
Ejemplares similares
-
Development and Validation of Embedded Device for Electrocardiogram Arrhythmia Empowered with Transfer Learning
por: Asif, Rizwana Naz, et al.
Publicado: (2022) -
Breast Cancer Detection and Classification Empowered With Transfer Learning
por: Arooj, Sahar, et al.
Publicado: (2022) -
A Hybrid Deep Learning Approach for ECG-Based Arrhythmia Classification
por: Madan, Parul, et al.
Publicado: (2022) -
Efficient Lightweight Multimodel Deep Fusion Based on ECG for Arrhythmia Classification
por: Hammad, Mohamed, et al.
Publicado: (2022) -
An ECG Stitching Scheme for Driver Arrhythmia Classification Based on Deep Learning
por: Kim, Do Hoon, et al.
Publicado: (2023)