<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

This study aimed to identify attitudes towards mental illness in pregnant female clients to clinics women in the province of Ramallah and Al Bireh, for this purpose applied to study procedures on a sample of (200) of pregnant mothers were selected a sample available, have reached results no statistically significant differences in the level of attitudes towards mental illness due to the variable age in mothers pregnant female clients to clinics for women. Ther were astatistically significant differences in the level of these trends depending on the variable-level scientific research for the benefit of pregnant class university students and older and then high school and so on all areas except the area of social interaction, The results a

BACKGROUND: In pregnancy, several physiological changes occur that lead to decrease in the level of hemoglobin. Anemia during pregnancy is a major public health concern in underdeveloped nations, with a high rate of morbidity and death among pregnant women. Inadequate prenatal care, a lack of information about the nutritional requirements of pregnant women, and general low socioeconomic circumstances all contribute to these high rates of morbidity and death. As pregnant women’s and husbands’ education levels increased, the frequency and severity of anemia decreased in the investigated community of pregnant women. AIM: This study aims to find out the level of knowledge about anemia in pregnancy among adult females attending pr

BACKGROUND: In pregnancy, several physiological changes occur that lead to decrease in the level of hemoglobin. Anemia during pregnancy is a major public health concern in underdeveloped nations, with a high rate of morbidity and death among pregnant women. Inadequate prenatal care, a lack of information about the nutritional requirements of pregnant women, and general low socioeconomic circumstances all contribute to these high rates of morbidity and death. As pregnant women’s and husbands’ education levels increased, the frequency and severity of anemia decreased in the investigated community of pregnant women. AIM: This study aims to find out the level of knowledge about anemia in pregnancy among adult females attending pr

Worldwide, hundreds of millions of people have been infected with COVID-19 since December 2019; however, about 20% or less developed severe symptoms. The main aim of the current study was to  assess  the  relationship  between  the  severity of Covid-19 and different clinical and laboratory parameters. A total number of 466 Arabs have willingly joined this prospective cohort. Out of the total number, 297 subjects (63.7%) had negative COVID-19 tests, and thus, they were recruited as controls, while 169 subjects (36.3%) who tested positive for COVID-19 were enrolled as cases. Out of the total number of COVID-19 patients, 127 (75.15%) presented with mild symptoms, and 42 (24.85%) had severe symptoms. The age range for the partic

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

One of the most serious health disasters in recent memory is the COVID-19 epidemic. Several restriction rules have been forced to reduce the virus spreading. Masks that are properly fitted can help prevent the virus from spreading from the person wearing the mask to others. Masks alone will not protect against COVID-19; they must be used in conjunction with physical separation and avoidance of direct contact. The fast spread of this disease, as well as the growing usage of prevention methods, underscore the critical need for a shift in biometrics-based authentication schemes. Biometrics systems are affected differently depending on whether are used as one of the preventive techniques based on COVID-19 pandemic rules. This study provides an

Thrombosis is a common clinical feature associated with morbidity and mortality in coronavirus disease-2019 (COVID-19) patients. Cytokine storm in COVID-19 increases patients' systemic inflammation, which can cause multiple health consequences. In this work, we aimed to indicate the effect of Pfizer-BioNTech vaccination on the modulation of monocyte chemoattractant protein-3 (MCP-3), matrix metalloproteinase 1 (MMP-1), and tumor necrosis factor-alpha (TNF-α) levels, and other systemic inflammatory biomarkers that associates with COVID-19 severity in patients who suffers from thrombosis consequences. For this purpose, ninety people were collected from Ibn Al-Nafees Hospital and divided into three groups each of which contained 30 people, 15

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121