Bladder dysfunction is one of the most common complications of diabetes, even exceeding nephropathy or peripheral neuropathy. Diabetic cystopathyaffects patients in both sexes, and its prevalence increases over time with diabetes; our concern is to evaluate the urodynamic findings of bladder dysfunction in diabetic patients.A cross sectional study conducted at Ghazi Al-Hariri Surgical specialized hospital during the period from the firsts of January 2018 to the end of Mar 2019, in which 118 diabetic patients (71 female and 47 male) with lower urinary tract symptoms were enrolled in the current study. The mean age (62±13) years old, 37.3% of patients presented with urgency as the main type of dysfunction. Diabetic cystopathy were fo

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

Abstract Introduction: Aphthous stomatitis is a recurring oral ulceration condition that affects a significant proportion of the population. While several factors have been proposed to contribute to its occurrence, the link between caffeine consumption, anxiety levels, and the development of aphthous stomatitis remains unknown. This survey-based study aimed to understand the association between coffee, anxiety, and the development of aphthous stomatitis in this specific demographic, which can provide useful insights for medical management as well as preventive strategies. Material and methods: A structured online questionnaire was distributed via various social media platforms targeting a sample of the Armenian population. The quest

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

Recurrent respiratory tract infections are responsible for about 85% of all diseases in childhood, and are associated with significant morbidity and mortality. The aim of this study is to evaluate the main causes underlying recurrent respiratory tract infections in 176 pediatric patients aged 2 month to 4 year and weight from 4 to11 kg referred to the child center hospital and Al-sader hospital prospective study.All parents were given information sheet which then analyzed and the percentage of incidence of causes were recorded, we found that higher % related to many causes; mostly related to the parent like poor family education, mother carelessness, incomplete vaccination, other related to empirical diagnosis, and short course of t

Coagulation is the most important process in drinking water treatment. Alum coagulant increases the aluminum residuals, which have been linked in many studies to Alzheimer's disease. Therefore, it is very important to use it with the very optimal dose. In this paper, four sets of experiments were done to determine the relationship between raw water characteristics: turbidity, pH, alkalinity, temperature, and optimum doses of alum [   .14 O] to form a mathematical equation that could replace the need for jar test experiments. The experiments were performed under different conditions and under different seasonal circumstances. The optimal dose in every set was determined, and used to build a gene expression model (GEP). The models were co

Background: Recently with improvement of dental implantology science, osseointegrated implants show a considerable durability, however; failures are not completely avoidable. Matrix metalloproteinase-2 (MMP-2) expression is disturbed in many pathological conditions such as peri-implantitis and periodontitis. This study was carried out to investigate the tissue expression of MMP-2 in the extracellular matrix of osseointegrated and diseased implants. Subjects and methods: Gingival biopsies were collected from six patients having osseointegrated or working implants and twenty with diseased or non osseointegrated implants and (6) controls having no implants. In situ hybridization technique was used to analyze the changes in immunoreactivity of