Background: Reflux laryngitis has gain a lot of attention in the last three decades as a possible explanation of idiopathic laryngeal problems.Acid suppressive therapy can
be of use in both the therapeutic and the diagnostic fields.The use of Omeprazole has proved to be of benefit in the diagnosis and treatment of reflux laryngitis.The
response to 12weeks course of Omeprazole is considered by many authors to be one of the diagnostic tooles of reflux laryngitis.
Aim: Is to study the effect of Omeprazole in the treatment of laryngeal manifestations of gastro-oesophageal reflux
Patients and methods: This is a prospective study of 37 patients attending Alkadhimiyah teaching hospital,department of otolalyn

Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

Background: Human teeth considered to be an important etiological host factor in relation to dental caries through its morphology and composition. Elements may incorporate in tooth structure during pre and post-eruptive period changing the resistance for caries. The aims of this study were to determine the concentration of selected major (Calcium and phosphorus) and trace elements (Ferrous iron, nickel, chromium and aluminum) in permanent teeth and enamel among a group of adolescent girls in relation to severity of dental caries Material and Methods: The study group consisted of 25 girls with an age of 13-15 years old referred by Orthodontists for extractions of upper first premolars (two sides). Tooth and enamel samples were prepared for

Background: Hypoxic ischemic encephalopathy (HIE) means failure to establish effective spontaneous breathing after complete delivery & leads to many changes if not diagnosed or treated immediately as mental retardation, cerebral palsy and epilepsy.
Objective: to study the demographic and clinical predictors of perinatal outcome in full term neonates with hypoxic ischemic encephalopathy.
Methods: Forty two neonates were diagnosed as cases of hypoxic ischemic encephalopathy by specialist pediatricians & admitted in Children Welfare Teaching Hospital & Al Kut Hospital in the period from January 2008 to March 2009. Predictors studied were sex, birth weight, Apgar scores at 1,5,15 min., meconium

     Hyperglycemia is a complication of diabetes (high blood sugar). This condition causes biochemical alterations in the cells of the body, which may lead to structural and functional problems throughout the body, including the eye. Diabetes retinopathy (DR) is a type of retinal degeneration induced by long-term diabetes that may lead to blindness. propose our deep learning method for the early detection of retinopathy using an efficient net B1 model and using the APTOS 2019 dataset. we used the Gaussian filter as one of the most significant image-processing algorithms. It recognizes edges in the dataset and reduces superfluous noise. We will enlarge the retina picture to 224×224 (the Efficient Net B1 standard) and utilize data aug

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

Background:The most common pattern of dyslipidemia in diabetic patients is increased triglyceride (TG) and decreased HDL cholesterol level, The concentration of LDL cholesterol in diabetic patients is usually not significantly different from non diabetic individuals, Diabetic patients may have elevated levels of non-HDL cholesterol [ LDL+VLDL]. However type 2 diabetic patients typically have apreponderance of smaller ,denser LDL particles which possibly increases atherogenicity even if the absolute concentration of LDL cholesterol is not significantly increased. The Third Adult Treatment Panel of the National Cholesterol Education Program (NCEP III) and the American Heart Association (AHA ) have designate diabetes as a coronary heart dis

The objective of this paper is to study the stability of SIS epidemic model involving treatment. Two types of such eco-epidemiological models are introduced and analyzed. Boundedness of the system is established. The local and global dynamical behaviors are performed. The conditions of persistence of the models are derived.