Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

The condition known as hypothyroidism is common in women, even in those who are fertile. The quantity and caliber of follicles present in the ovary at any one moment are known as the ovarian reserve. Individuals who are susceptible to a decreased ovarian reserve ought to have an assessment of their ovarian reserve conducted. The purpose of this research is to assess the impact of hypothyroidism on Iraqi women's ovarian reserve using Inhibin B hormone and hormone tests FSH, LH. There was no discernible variation in the average (±SD) age from (20 to 40) years of the patient group compared to the control group (p-value 0.08). However the mean BMI of the patients were statistically significantly different from the controls (P- value 0.006).Wom

BACKGROUND. KI-67 (MKI-67 in humans) is a protein able to bind to DNA which contributes to cell growth and cell proliferation. KI-67 is currently considered as a biomarker that is widely utilized as prognostic indicator for evaluating cell proliferation, diagnosing diseases, and conducting research. Several different kinds of cancer have high Ki-67 expression, which simplifying the choice of treatment for individuals with various cancer types.AIM. The objective was to evaluate the expression of KI67 in patients suffering papillary thyroid cancer (PTC) also the association between patients age and gender and KI67 expression.MATERIALS AND METHODS. To undertake an in-

Document clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of this paper is to present an up-to-date and self-contained review fully devoted to document clustering via evolutionary algorithms. It firstly provides a comprehensive inspection to the document clustering model revealing its various components with its related concepts. Then it shows and analyzes the principle research wor

              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter

Table tennis is considered one of the fast base sports that the player needs to have the speed of performance and awareness, especially in straight forward and back strikes, which is an important offensive skills, and the player success depends on his perception speed to the point of the fall of the ball in the arena of his competitor. But there is no way to measure cognitive processing speed. Therefore, the researchers sought to design a test that measures this ability to ensure its scientific evaluation, and then establish standard scores for this test for the players of the specialized school of table tennis, to help evaluate them objectively and move away from subjective estimates when evaluating and developing measuring instruments in

Inherited metabolic disorders (IMDs) are a diverse group of hereditary abnormalities that leads to a defect in metabolic pathway. Its diagnosis has been transformed by the innovations of molecular genetics and computational biology. Conventionally, diagnosis of IMDs is dependent on clinical findings and biochemical tests. Yet, these methods are limited due to a heterogeneity of such disorders and a large number of genes involved. The main objective of this review is to highlight the role of next-generation sequencing (NGS), including targeted gene panels, whole-exome sequencing (WES), and whole-genome sequencing (WGS), in the diagnosis of IMDs and providing reliable information in identifying genetic causes, and to explore the integrated an