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A Multistage Deep Learning Algorithm for Detecting Arrhythmia
(Institute of Electrical and Electronics Engineers, 2018)
Deep Belief Networks (DBN) is a deep learning algorithm that has both greedy layer-wise unsupervised and supervised training. Arrhythmia is a cardiac irregularity caused by a problem of the heart. In this study, a multi-stage ...
Makine Öğrenmesini Kullanarak Solunum Sesinin Analizinin Değerlendirilmesi
(Institute of Electrical and Electronics Engineers Inc., 2017)
Solunum seslerinin oskültasyonu, pulmoner
bozukluklar ve bazı kardiyak bozuklukların teşhisi için
göğüs ve sırttan dinlenen sesler için kullanılan ucuz ve etkili bir yöntemdir. Günümüzde bilgisayar destekli analiz ve ...
A new approach to early diagnosis of congestive heart failure disease by using Hilbert-Huang transform
(Elsevier Ireland Ltd., 2016)
Congestive heart failure (CHF) is a degree of cardiac disease occurring as a result of the heart's inability to pump enough blood for the human body. In recent studies, coronary artery disease (CAD) is accepted as the most ...
Deep learning with 3D-second order difference plot on respiratory sounds
(Elsevier, 2018)
The second order difference plot (SODP) is a nonlinear signal analysis method that visualizes two consecutive data points for many types of biomedical signals. The proposed method is based on analysing quantization of ...
Deep Learning for COPD Analysis Using Lung Sounds
(Baku State University, 2018)
In this study, Hilbert-Huang Transform (HHT) was applied to the lung sounds from RespiratoryDatabase@TR and the statistical features were calculated from the different modulations of the HHT. The statistical features were ...
SecureDeepNet-IoT: A deep learning application for invasion detection in industrial Internet of Things sensing systems
(Wiley, 2021)
Deep learning (DL) is a special field of artificial intelligence that has increased its use in various fields and has proved its effectiveness in classification. The feasibility of using many hidden layers and many neurons ...
A deep learning architecture for identification of breast cancer on mammography by learning various representations of cancerous mass
(Springer, 2021)
Deep Learning (DL) is a high capable machine learning algorithm with the detailed analysis abilities on images. Although DL models achieve very high classification performances, the applications are trending on using and ...
ECG based human identification using Second Order Difference Plots
(Elsevier, 2019)
Background and objective: ECG is one of the biometric signals that has been studied in peer-reviewed over past years. The developments on the signal analysis methods show that the studies on the ECG would continue unabatedly. ...
A fully distributed energy-aware multi-level clustering and routing for WSN-based IoT
(Wiley, 2021)
One of the major problems in wireless sensor networks (WSNs) is that resource-constrained sensor nodes consume their limited batteries quickly due to long-distance data communications. The communication distance of the ...
A novel fractional operator application for neural networks using proportional Caputo derivative
(Springer, 2022)
In machine learning models, one of the most popular models is artificial neural networks. The activation function is one of the important parameters of neural networks. In this paper, the sigmoid function is used as an ...