Deep Transfer Learning for Chronic Obstructive Pulmonary Disease Detection Utilizing Electrocardiogram Signals
The motivation of this research is to introduce the first research on automated Chronic Obstructive Pulmonary Disease (COPD) diagnosis using deep learning and the first annotated dataset in this field. The primary objective and contribution of this research is the development and design of an artifi...
Main Authors: | Inanc Moran, Deniz Turgay Altilar, Muhammed Kursad Ucar, Cahit Bilgin, Mehmet Recep Bozkurt |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10107390/ |
Similar Items
-
A new diagnostic method for chronic obstructive pulmonary disease using the photoplethysmography signal and hybrid artificial intelligence
by: Engin Melekoglu, et al.
Published: (2022-12-01) -
Quantized Information in Spectral Cyberspace
by: Milton A. Garcés
Published: (2023-02-01) -
Wavelet Transform-Statistical Time Features-Based Methodology for Epileptic Seizure Prediction Using Electrocardiogram Signals
by: Andrea V. Perez-Sanchez, et al.
Published: (2020-11-01) -
Adaptive Filtering Strategy to Remove Noise from ECG Signals Using Wavelet Transform and Deep Learning
by: Saber Fooladi, et al.
Published: (2020-12-01) -
Convolutional transformer-driven robust electrocardiogram signal denoising framework with adaptive parametric ReLU
by: Jing Wang, et al.
Published: (2024-02-01)