Background: Globally, hepatitis B is one of the most common infectious diseases. Estimates indicate that at least 2 billion people have been infected with the hepatitis B virus (HBV), with more than 378 million people being chronic carriers. Those individuals at higher risk for acquiring HBV and transmitting disease like pregnant women should be screened for hepatitis B surface antigen (HBsAg) to prevent transmission by vaccination and operation. Aim of study: The aim of this study was to determine the prevalence of HBsAg and its associated parameters in pregnant women who referred to antenatal clinic in Baghdad Province. Methods: The 234 apparently healthy pregnant women and their families, husbands and children were se

The need for cloud services has been raised globally to provide a platform for healthcare providers to efficiently manage their citizens’ health records and thus provide treatment remotely. In Iraq, the healthcare records of public hospitals are increasing progressively with poor digital management. While recent works indicate cloud computing as a platform for all sectors globally, a lack of empirical evidence demands a comprehensive investigation to identify the significant factors that influence the utilization of cloud health computing. Here we provide a cost-effective, modular, and computationally efficient model of utilizing cloud computing based on the organization theory and the theory of reasoned action perspectives. A tot

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The current research aims to identify the types and rates and the reasons for the crimes that are with the origin and sexual scattered deviation between the fabric of Iraqi society, which reticent about because of the culture of the community, where he offered a researcher investigator justice and tribal leaders and lawyers about proportion and the types and causes of crime is the origin of sexual deviance and finally a question asked a researcher in 1000 young lived their adolescence days of the former regime (1979-2003) from going to brothels researcher found that 920 people and 92% had gone to the house to practice adultery and that 70 of them, and by 7% had engaged in masturbation only and that 10 of them have not committed anything

<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 convol

<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 convol

The COVID-19 pandemic has had a huge influence on human lives all around the world. The virus spread quickly and impacted millions of individuals, resulting in a large number of hospitalizations and fatalities. The pandemic has also impacted economics, education, and social connections, among other aspects of life. Coronavirus-generated Computed Tomography (CT) scans have Regions of Interest (ROIs). The use of a modified U-Net model structure to categorize the region of interest at the pixel level is a promising strategy that may increase the accuracy of detecting COVID-19-associated anomalies in CT images. The suggested method seeks to detect and isolate ROIs in CT scans that show the existence of ground-glass opacity, which is fre