Preferred Language
Articles
/
SBbkBIcBVTCNdQwCIS0T
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
...Show More Authors

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convolutional neural network that uses other activation functions (exponential linear unit (ELU), rectified linear unit (ReLU), Swish, Leaky ReLU, Sigmoid), and the result is that utilizing CWNN gave better results for all performance metrics (accuracy, sensitivity, specificity, precision, and F1-score). The results obtained show that the prediction accuracies of CWNN were 99.97%, 99.9%, 99.97%, and 99.04% when using wavelet filters (rational function with quadratic poles (RASP1), (RASP2), and polynomials windowed (POLYWOG1), superposed logistic function (SLOG1)) as activation function, respectively. Using this algorithm can reduce the time required for the radiologist to detect whether a patient has COVID or not with very high accuracy.</p>

Crossref
View Publication
Publication Date
Thu Jan 01 2026
Journal Name
Desalination And Water Treatment
Microplastics toxicity: Classification, sources, exposure routes, and experiments
...Show More Authors

Microplastics (MPs), including polymers such as polyethylene, polyvinyl chloride (PVC), and polystyrene (PS), are widespread environmental contaminants detected in air, water, soil, and food. These particles originate from the breakdown of larger plastics and from direct industrial and consumer sources, including packaging, textiles, and personal care products. MPs enter the human body primarily through ingestion, inhalation, and dermal contact, with food, water, and air serving as major exposure pathways. Once internalized, MPs have been found in various human tissues and biological fluids, indicating their capacity for bioaccumulation. Toxicological studies in experimental models and occupational settings link MP exposure to oxidative str

... Show More
View Publication Preview PDF
Scopus Crossref
Publication Date
Thu Feb 24 2022
Journal Name
Journal Of Educational And Psychological Researches
Question Asking Skills: Levels, Conditions, Classification, and Types
...Show More Authors

The research aims to know the question asking skills in terms of levels, conditions, classification, and types. The research limited to the literature that dealt with the importance of questioning for students and teachers. The most important term used in the research is the skill (Ryan defined it as "the ability to perform with great efficiency, accuracy, and ease). The results of the research are as follows: 1. the questions asked by the schoolteacher within the assessment of students' learning. 2. Teachers should focus on the lower levels of learning (remembering, understanding and comprehension) and then evaluating students at the higher levels (synthesis and evaluation). 3. Teacher with good knowledge can skillfully use the question

... Show More
View Publication Preview PDF
Publication Date
Fri Jun 02 2023
Journal Name
East European Journal Of Physics
Reevaluation Body Weight and Age with Standardized Uptake Value in the Liver Cancer for [18F] FDG PET/CT
...Show More Authors

Standardized uptake values, often known as SUVs, are frequently utilized in the process of measuring 18F-fluorodeoxyglucose (FDG) uptake in malignancies . In this work, we investigated the relationships between a wide range of parameters and the standardized uptake values (SUV) found in the liver.  Examinations with 18F-FDG PET/CT were performed on a total of 59 patients who were suffering from liver cancer. We determined the SUV in the liver of patients who had a normal BMI (between 18.5 and 24.9) and a high BMI (above 30) obese. After adjusting each SUV based on the results of the body mass index (BMI) and body surface area (BSA) calculations, which were determined for each patient based on their height and weight. Under a variety of dif

... Show More
View Publication
Scopus (2)
Crossref (1)
Scopus Clarivate Crossref
Publication Date
Sat Dec 31 2022
Journal Name
Al-kindy College Medical Journal
Comparative study on Various Tube Voltages and Contrast Media Doses in CT Pulmonary Angiography to detect Pulmonary Thromboembolism
...Show More Authors

Background: Lowering the amount of iodinated contrast material and tube voltage may increase pulmonary artery opacification and thrombus identification without compromising picture quality.

Objectives: To explore the efficiency of using lower tube voltage and a lower contrast medium dose for conducting computed tomography for pulmonary angiography (CTPA) aiming to increase its accuracy in detecting pulmonary thromboembolism (PTE).

Subjects and Methods:100 patients scheduled for CTPA with a preoperative diagnosis of PTE were grouped into two: group A, (50 patients) got 1 mL/kg at 120 kV and group B, (50 patients) received 0.5 mL/kg at 80 kV.The tec

... Show More
View Publication Preview PDF
Crossref
Publication Date
Mon Dec 01 2008
Journal Name
Journal Of Economics And Administrative Sciences
Neural Networks as a Discriminant Purposes
...Show More Authors

Discriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.

In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.  

 

 

View Publication Preview PDF
Crossref
Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Biochemical Study on the Impact of Radiation-induced Oxidative Stress on Radiographers in the X-ray and CT-scan Departments
...Show More Authors

The consequences of ionizing radiation-induced oxidative stress on radiographers in X-ray and CT-scan departments utilizing several biochemical were analyzed. The study found highly considerable discrepancies in the interplay between radiation levels and gender in terms of mean Malondialdehyde (MAD), Vitamin D3 (Vit.D3), Triiodothyronine (T3), Thyroxine (T4), and High-Density Lipoprotein (HDL), but not Thyroid Stimulating Hormone (TSH), cholesterol, triglyceride (TG) and Low-Density Lipoprotein (LDL). The findings indicated that malondialdehyde is a useful biomarker for assessing oxidative stress in radiographers with exposure to ionizing radiation.

View Publication Preview PDF
Scopus (3)
Scopus Crossref
Publication Date
Mon Jan 01 2018
Journal Name
Lecture Notes Of The Institute For Computer Sciences, Social Informatics And Telecommunications Engineering
Sensor Data Classification for the Indication of Lameness in Sheep
...Show More Authors

View Publication Preview PDF
Scopus (6)
Crossref (1)
Scopus Clarivate Crossref
Publication Date
Tue Sep 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Two-Stage Classification of Breast Tumor Biomarkers for Iraqi Women
...Show More Authors

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are

... Show More
View Publication Preview PDF
Publication Date
Sun Jan 10 2016
Journal Name
British Journal Of Applied Science &amp; Technology
The Effect of Classification Methods on Facial Emotion Recognition ‎Accuracy
...Show More Authors

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

... Show More
View Publication Preview PDF
Crossref (2)
Crossref
Publication Date
Thu Sep 15 2022
Journal Name
Knowledge And Information Systems
Multiresolution hierarchical support vector machine for classification of large datasets
...Show More Authors

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

... Show More
View Publication
Scopus (6)
Crossref (4)
Scopus Clarivate Crossref