Background: Diabetes mellitus (DM) is a significant cause of visual impairment; many diabetics do not have regular eye examinations, although it is known that early diagnosis and reduces the risk of blindness. There were many barriers that prevent diabetics from attending eye clinics.

Objectives: To assess knowledge, and practice about ocular complications among diabetic patients and to determine barriers preventing the diabetic patients annual visual checking

Methods: A cross-sectional study involving the interview was conducted among 300 diabetic patients attending out patient in Ibn Al Haitham Teaching Ophthalmology Hospital between November 2017 and June 2018.

BACKGROUND: Vaccine hesitancy and reluctant had an important obstacle in achieving protection and population immunity against coronavirus disease 19 (COVID-19). It is essential to achieve high COVID-19 vaccination acceptance rates among medical students and health care workers to provide recommendations and counseling vaccine hesitant population. AIM: This study aims to identify level of COVID-19 hesitancy, attitude, knowledge, and factors that affect vaccination decision. MATERIALS AND METHODS: A cross-sectional study was done among medical students in Al-Kindy College of Medicine, University of Baghdad, Baghdad, Iraq. Data collection was done through an online Google Forms questionnaire during 2021 from 810 medical students.

The present study aimed to look for the differences in the oxidative stress status in sera and saliva samples of type 2 diabetic Iraqi patients with and without proliferative diabetic retinopathy. As well as to look for the possibility whether this status can be measured in saliva as an alternative sample to that of serum, hence to achieve that total oxidant status, total antioxidant status and oxidative stress index were measured in both sera and saliva samples of two groups of patients with type 2 diabetes mellitus and the healthy individuals. Upon the comparison between patients without proliferative diabetic retinopathy and the control sample the results showed presence of a significant increase (p < 0.05) of total oxidant st

Background: The influence of glucose metabolism is seen in many infectious diseases, making  diabetic patients more vulnerable to sepsis and other serious sequelae of bacterial invasion such as UTI and vaginitis.Patients and method: sixty two patients (women) were suffering from GUTIs consulting Al-Elwya hospital from November- 2009 to March -2010. Two samples were taken from those patients (urine samples and vaginal swabs); these samples were cultured on Blood, Chocolate, and MacConkey's agar for isolation of bacteria.Results: The study group consists of sixty two women suffering from (GUTI), their ages range from 18-55 years. Thirty eight of them were diabetic women and twenty four of them were non- diabetic women. Twenty t

A total of 258 voluntary blood donors (males 101; females 157) in the age range of 18-52 yr among males and 18-55 yr among females were examined for Toxoplasma gondii antibodies (IgG), and (IgM) by immunological technique (Enzyme linked Immunosorbant Assay) during the period from March 2009 to April 2010. This study covered a wide range of factors including immunological, age ,sex , place of residence and symptoms that may have a possible relationship with toxoplasmosis. Results presented in this study showed clearly that 38 (14.7%) of individuals participated in this study having IgG Toxoplasma Ab, among those 10 samples (9.9%) were males and 28 samples (17.8%) were females. Moreover, we found the prevalence of IgM seropositivity in th

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

This study deals with thirty non-insulin dependent diabetes mellitus patients suffering from diabetic nephropathy in addition to twenty five healthy control.Some biochemical parameters were determined in the serum of all subjects enrolled in the study.These parameters are serum glucose,serum urea,serum creatinine,total serum protein and serum albumin.The aim of the present study was to estimate these parameters in diabetic nephropathy patients. The results of the present study revealed a significant increase in glucose,urea and creatinine in patients as compared to controls . Also a significant decrease was found in total serum protein, serum albumin and albumin to globulin ratio (A/G) in patients compared to controls,whi