Background Birth defects are one of the causes of pediatric disability and mortality in all around the world. Data on birth defects from population-based studies originating from developing countries are lacking. Cleft lip (CL), cleft lip and palate (CLP), and isolated cleft palate (CP), collectively termed oral clefts, occur in all races, both sexes, and all socioeconomic groups and vary internationally (1). The main aim of this research is to establish the frequency of cleft lip and/or palate in the population of the Al-Ramadi City, and to characterize the demographic features of affected individuals and find possible risk factors. Materials and methods We conducted a survey of the Educational Maternal and Pediatric Hospital in Al-Ramadi

Alopecia areata is considered as a major health problem, its importance is attributed to its
recent increased incidence in our population. Till now, there is no exact cause for alopecia areata
although researchers thought it's an autoimmune disease.
This clinical study was designed to evaluate the role of trace elements (zinc and copper) in patients
with alopecia areata. Twenty patients were diagnosed as having alopecia areata with an age range
(10-40 years) were involved in this study. Normal subjects of the same age group were also
evaluated as control. The level of serum Zn and Cu were measured by flame atomic absorption
spectrophotometry in both control and patient group. And the ratio of Zn/Cu was also estimated

Background: Oxidative stress is a deleterious process that can be an important mediator of damage to cell structures and consequently various disease states. Exposure to free radicals from a variety of sources has led organisms to produce a series of defense mechanisms. The antioxidant ceruloplasmin is a copper-containing ferroxidase that can oxidize ferrous iron (Fe2+) to its nontoxic ferric (Fe3+) form. Ferrous iron (Fe2+) is extremely damaging because of its ability to generate toxic free radicals. Oral lichen planus (OLP) is a chronic inflammatory oral mucosal disease of unknown etiology. Previous studies reported that reactive oxygen species may be involved in the pathogenesis of lichen planus. The aim of this study was to estimate the

The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

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Abstract: Background: Prediabetes and are increasing in prevalence all over the world, they each carry risks to the future development of diabetes mellitus and cardiovascular disease. These risks will be greatly exaggerated if they occur together in the same individual. The aim of the study was to find the prevalence and the association of prediabetes and metabolic syndrome, in addition to analyzing the correlation of the risk factors that lead to their development. Material and Methods: This was a cross-sectional, simple random study that included 300 Iraqi individuals, aged between 30-75 years, who accepted to take part in this study were recruited. Result: Prevalence of prediabetes and metabolic syndrome was (33.66%) and (42%) r

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.