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Diagnosis of COVID-19 Infection via Association Rules of Cough Encoding
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Article information: COVID-19 has roused the scientic community, prompting calls for immediate solutions to avoid the infection or at least reduce the virus's spread. Despite the availability of several licensed vaccinations to boost human immunity against the disease, various mutated strains of the virus continue to emerge, posing a danger to the vaccine's ecacy against new mutations. As a result, the importance of the early detection of COVID-19 infection becomes evident. Cough is a prevalent symptom in all COVID-19 mutations. Unfortunately, coughing can be a symptom of various of diseases, including pneumonia and inuenza. Thus, identifying the coughing behavior might help clinicians diagnose the COVID-19 infection earlier and distinguish coronavirus-induced from non-coronavirus-induced coughs. From this perspective, this research proposes a novel approach for diagnosing COVID-19 infection based on cough sound. The main contributions of this study are the encoding of cough behavior, the investigation of its unique characteristics, and the representation of these traits as association rules. These rules are generated and distinguished with the help of data mining and machine learning techniques. Experiments on the Virufy COVID-19 open cough dataset reveal that cough encoding can provide the desired accuracy (100%).

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Publication Date
Tue Jul 06 2010
Journal Name
Journal Of College Of Education
Association Between lnsulin Resistance And Diabetes Mellitus
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Background: Obesity and diabetes mellitus are the common health problems,and obesity is common cause of the insulin resistance. Aim of studv: Aim of the study is to find any correlation between obesity (insulin resistance) and type I diabetes in children. Patients and methods: This study included (40) children with type I diabetes, in addition to (40) children as control.The age of all studied groups ranged from (8-18) years.This study was attemted from Ibn AlBalady Hospital during from 20 August to 9 Novembar,2008. The subjects wrer divided into (4) groups according to their BMI:- * Obese children,diabetes,n=2O,BMI>30. * Non obese children, diabetes, n=20,BMI<25. Obese children, non diabetes, n=20,BMI>30. * Non obese children,non diabetes

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Publication Date
Thu Jun 30 2016
Journal Name
Al-kindy College Medical Journal
Association between HLA and Guillain Barre' syndrome
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Background: Genetic factors play an important role in susceptibility to Guillain Barre' syndrome. Human leukocyte antigen (HLA) as part of immune system has a role in the disease process.Aim of the study: to assess the relationship between HLA-A alleles with Guillain Barre' syndrome (GBS) compared with a healthy control group using PCR-SSOP method.Type of the study: Cross-sectional study.Patients and methods:Patient's group consisted of 30 Iraqi Arab Muslims patients with Guillain Barre' syndrome that consulted the Neurological department in Neurosciences Hospital between January-2013 to January- 2014 were genotyped for HLA-A alleles. A control group consisted of 30 healthy volunteers among the staff of AL-Kindi College of Medicine that

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Publication Date
Mon Jun 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Breast Tumor Diagnosis Using Diode Laser in Near Infrared Region
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In the last years, new non-invasively laser methods were used to detect breast tumors for pre- and postmenopausal females. The methods based on using laser radiation are safer than the other daily used methods for breast tumor detection like X-ray mammography, CT-scanner, and nuclear medicine.  

      One of these new methods is called FDPM (Frequency Domain Photon Migration). It is based on the modulation of laser beam by variable frequency sinusoidal waves. The modulated laser radiations illuminate the breast tissue and received from opposite side.

      In this paper the amplitude and the phase shift of the received signal were calculated according to the orig

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Publication Date
Sat Apr 05 2025
Journal Name
2025 Ieee 4th International Conference On Computing And Machine Intelligence (icmi)
From Pixels to Diagnosis: AI-Powered CNN for Pneumonia Detection
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Publication Date
Fri Aug 21 2026
Journal Name
International Journal Of Nutrology
Metabolomics unleashed: transforming disease diagnosis and treatment with molecular insights
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Introduction: Metabolism is a vital technique in the field of medical research. It offers an insight into the etiopathogenesis of diseases and the formulation of personalized treatment regimens. Biochemical and metabolic alterations require innovative therapeutic approaches in polycystic ovarian syndrome (PCOS). Trace elements, like copper and zinc, may help treat PCOS due to their relation to metabolism. Objective: The aim of this work was to explore the metabolic impact of copper and zinc supplementation in women with PCOS using state-of-the-art metabolomics technologies. Methods: This study included fifty PCOS patients and fifty healthy subjects. High-resolution mass spectrometry (HRMS) and nuclear magnetic resonance

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Publication Date
Sun Oct 03 2010
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Genitourinary tract infection in diabetic women: Bacteriological study
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Background: The influence of glucose metabolism is seen in many infectious diseases, making  diabetic patients more vulnerable to sepsis and other serious sequelae of bacterial invasion such as UTI and vaginitis.Patients and method: sixty two patients (women) were suffering from GUTIs consulting Al-Elwya hospital from November- 2009 to March -2010. Two samples were taken from those patients (urine samples and vaginal swabs); these samples were cultured on Blood, Chocolate, and MacConkey's agar for isolation of bacteria.Results: The study group consists of sixty two women suffering from (GUTI), their ages range from 18-55 years. Thirty eight of them were diabetic women and twenty four of them were non- diabetic women. Twenty t

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Publication Date
Mon Nov 01 2021
Journal Name
Archives Of Razi Institute
Effect of Leishmania major infection on the expression of TGF beta in murine
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Leishmania major is a protozoan parasite that causes cutaneous Leishmaniasis disease in human beings and animals. The disease is prevalent in tropical and semitropical countries and has great health importance. The present study aimed to identify the histological changes in the organs infected with L. major and to provide a sophisticated diagnostic method for infection through detecting TGF-β cytokine by immunohistochemistry technique(IHC) from October 2020 to January 2021. A total of 40 samples of paraffin blocks were used for different organs including skin, spleen, liver, kidney, and heart of male and female BALB/c mice, aged 6-8 weeks, which were previously infected subcutaneously with L. major promastigotes at a dose of 1×107 promast

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Evaluation of training programs directed toward the diagnosis of the phenomenon of financial and administrative corruption
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 Abstract

It considers training programs is an important process contributing to provide employees with the skills required to do their jobs efficiently and effectively, so it should be concerned with and the focus of all government our organizations, and perhaps the most important reasons that I was invited to select the subject (evaluation of training programs directed toward the diagnosis of the phenomenon of financial and administrative corruption) It is the importance of those programs working in the regulatory institutions General and the Office of Inspector General of Finance and the Ministry particularly for employees because of their role in the development of their skills and their experience and their beha

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Publication Date
Wed Jan 01 2025
Journal Name
Iv. International Rimar Congress Of Pure, Applied Sciences
A New Intrusion Detection Approach Based on RNA Encoding and K-Means Clustering Algorithm Using KDD-Cup99 Dataset
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Intrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the dis

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Publication Date
Sat Nov 05 2016
Journal Name
Research Journal Of Applied Sciences, Engineering And Technology
Image Compression Based on Cubic Bezier Interpolation, Wavelet Transform, Polynomial Approximation, Quadtree Coding and High Order Shift Encoding
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In this study, an efficient compression system is introduced, it is based on using wavelet transform and two types of 3Dimension (3D) surface representations (i.e., Cubic Bezier Interpolation (CBI)) and 1 st order polynomial approximation. Each one is applied on different scales of the image; CBI is applied on the wide area of the image in order to prune the image components that show large scale variation, while the 1 st order polynomial is applied on the small area of residue component (i.e., after subtracting the cubic Bezier from the image) in order to prune the local smoothing components and getting better compression gain. Then, the produced cubic Bezier surface is subtracted from the image signal to get the residue component. Then, t

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