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Article
Automated retinal disease classification using hybrid transformer model (SViT) using optical coherence tomography images
Optical coherence tomography (OCT) is a widely used imaging technique in ophthalmology for diagnosis and treatment. Recent advances in deep neural networks (DNNs) and vision transformers (ViTs) have paved the ...
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Article
Open AccessDiabetic Foot Ulcer Detection: Combining Deep Learning Models for Improved Localization
Diabetes mellitus (DM) can cause chronic foot issues and severe infections, including Diabetic Foot Ulcers (DFUs) that heal slowly due to insufficient blood flow. A recurrence of these ulcers can lead to 84% o...
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Chapter
Development of Low Cost, Automated Digital Microscopes Allowing Rapid Whole Slide Imaging for Detecting Malaria
Plasmodium parasites are responsible for the life-threatening illness known as malaria, which remains a significant public health problem across the world, especially in areas with limited access to resources....
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Article
Automated semantic lung segmentation in chest CT images using deep neural network
Lung segmentation algorithms play a significant role in segmenting theinfected regions in the lungs. This work aims to develop a computationally efficient and robust deep learning model for lung segmentation u...
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Article
NFU-Net: An Automated Framework for the Detection of Neurotrophic Foot Ulcer Using Deep Convolutional Neural Network
Neurotrophic Foot Ulcer (NFU) is most common in patients with diabetes mellitus, and it may result in amputation of the lower extremity (leg and foot). Current methods used for NFU diagnosis are highly complex...
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Article
A deep learning approach for Parkinson’s disease diagnosis from EEG signals
An automated detection system for Parkinson’s disease (PD) employing the convolutional neural network (CNN) is proposed in this study. PD is characterized by the gradual degradation of motor function in the br...
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Chapter and Conference Paper
Analysis of Electrocardiogram (ECG) Signals for Human Emotional Stress Classification
Electrocardiogram (ECG) signal significantly reflects autonomic nervous system (ANS) activities during emotional stress changes. Undeniably, a variety of valuable information can be extracted from a single rec...
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Chapter and Conference Paper
EMG Signal Based Human Stress Level Classification Using Wavelet Packet Transform
Recent days, Electromyogram (EMG) signal acquired from muscles can be useful to measure the human stress levels. The aim of this present work to investigate the relationship between the changes in human stress...