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Efficient COVID-19 Segmentation from CT Slices Exploiting Semantic Segmentation with Integrated Attention Mechanism
(Sprınger, 2021)
Coronavirus (COVID-19) is a pandemic, which caused suddenly unexplained pneumonia cases and caused a devastating effect on global public health. Computerized tomography (CT) is one of the most effective tools for COVID-19 ...
Prediction of intrapartum fetal hypoxia considering feature selection algorithms and machine learning models
(Sprınger, 2019)
Introduction Cardiotocography (CTG) consists of two biophysical signals that are fetal heart rate (FHR) and uterine contraction (UC). In this research area, the computerized systems are usually utilized to provide more ...
Computer-Aided Diagnosis System of Fetal Hypoxia Incorporating Recurrence Plot With Convolutional Neural Network
(Frontıers Medıa Sa, 2019)
Background: Electronic fetal monitoring (EFM) is widely applied as a routine diagnostic tool by clinicians using fetal heart rate (FHR) signals to prevent fetal hypoxia. However, visual interpretation of the FHR usually ...
DCCMED-Net: Densely connected and concatenated multi Encoder-Decoder CNNs for retinal vessel extraction from fundus images
(Churchıll Lıvıngstone, 2020)
Recent studies have shown that convolutional neural networks (CNNs) can be more accurate, efficient and even deeper on their training if they include direct connections from the layers close to the input to those close to ...
Efficient approach for digitization of the cardiotocography signals
(Elsevıer, 2020)
Cardiotocography (CTG) is generally provided on printed traces, and digitization of CTG signal is important for forthcoming assessments. In this paper, a new algorithm relies on the box-counting method is offered for the ...
Computer-aided diagnosis system combining FCN and Bi-LSTM model for efficient breast cancer detection from histopathological images
(Elsevıer, 2019)
Breast cancer (BC) is one of the most frequent types of cancer that adult females suffer from worldwide. Many BC patients face irreversible conditions and even death due to late diagnosis and treatment. Therefore, early ...
Normal and Acute Tympanic Membrane Diagnosis based on Gray Level Co-Occurrence Matrix and Artificial Neural Networks
(Ieee, 2019)
Otitis Media (OM) is the general name of middle ear inflammation. In order to diagnose this disease, it is important to examine the middle ear tympanic membrane (TM) by a standard otoscopy device. In recent years, biomedical ...
White Blood Cell Classification Based on Shape and Deep Features
(Ieee, 2019)
Classification of the white blood cells (WBCs) in blood smear images is essential for providing important information to the physicians. In addition, manual analyzing of the blood smear images for determining the various ...
The Influences of Different Window Functions and Lengths on Image-based Time-Frequency Features of Fetal Heart Rate Signals
(Ieee, 2018)
In the clinical practice, the fetal distress conditions such as hypoxia are detected routinely during antepartum and even intrapartum periods with the help of electronic fetal monitoring device, often called Cardiotocography ...
Intelligent System based on Genetic Algorithm and Support Vector Machine for Detection of Myocardial Infarction from ECG signals
(Ieee, 2018)
Myocardial Infarction (MI) is one of the well-known heart attacks. This cardiac abnormality occurs when the artery connecting the heart is blocked. The main aim of this paper is to identify electrocardiogram (ECG) signals ...
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