Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

Background: A diverse group of bacteria live in biofilms in the oral cavity. On dental surfaces biofilms form plaque that is potentially involved in caries and periodontal diseases. Periodic studying of plaque microflora and their antimicrobial sensitivity patterns strongly affects the clinical practice in plaque-induced oral diseases. Materials and methods: Dental plaque samples were collected from 22 patients having ages ranged between 33 and 49 years with gingivitis that met the study criteria. Plaque, gingival and gingival bleeding indices (PI, GI, GBI) were measured for each patient. Laboratory procedures included microbiological examination of plaque samples followed by antibiotic sensitivity testing using disc diffusion method were

Soil compaction is one of the most harmful elements affecting soil structure, limiting plant growth and agricultural productivity. It is crucial to assess the degree of soil penetration resistance to discover solutions to the harmful consequences of compaction. In order to obtain the appropriate value, using soil cone penetration requires time and labor-intensive measurements. Currently, satellite technologies, electronic measurement control systems, and computer software help to measure soil penetration resistance quickly and easily within the precision agriculture applications approach. The quantitative relationships between soil properties and the factors affecting their diversity contribute to digital soil mapping. Digital soil maps use

Background: Polycystic ovary syndrome (PCOS) is the most common endocrine abnormality in women, there is an increasing evidence for an oxidative stress in PCOS that induce genomic and mitochondrial deoxyribonucleic acid damage that leads directly to reduced fertility. The objectives of this study are to assess and compare the periodontal health status by measuring clinical periodontal parameters (PLI, GI and BOP)as well as serum levels of superoxide dismutase at gingivitis ,gingivitis with PCOS and healthy periodontium groups, then correlate between clinical and biochemical parameters. Materials and Methods: 60 females with an age range between (25-40) years old had been tested and divided into3 groups ,the control group consists of (20) f

Forty six Iraqi women with PCOS were involved in this study . They were treated with metformin alone and with antioxidant agents (vitamin E or C).It was found that all patients who treated with metformin or with combination of metformin with antioxidant agents showed significant decrease in hirsutism score. The treatment of metformin with antioxidant agents is of great benefit in treatment of hirsutism in PCOS due to that there was no worsening effect after treatment. This may indicate that antioxidant agents may participate in alleviation of hirsutism so it can be said that oxidative stress may play an important role in developing of hirsutism in PCOS.   

Abdominal fat synthesizes a variety of adipokines, including vaspin and chemerin, that affect the resistance to insulin. This research was conducted to demonstrate the effect of pioglitazone, one insulin sensitizer used to decrease insulin resistance, on these adipokines in   obese patients with polycystic ovary (PCOS). Twenty-five obese women with PCOS were treated with pioglitazone 15mg/bid for 12 weeks. Modifications in fasting blood glucose (FBG), serum fasting insulin (FSI), chemerin and vaspin serum levels, follicle stimulation hormone (FSH), luteinizing hormone (LH), testosterone (T), and in baseline and post-therapy were assessed. Body mass index decreased without any substantial variance after 12 weeks of piogl

Abstract

Objective(s): A descriptive study aimed to determine nurses' knowledge about chest physiotherapy techniques for patients with Corona virus disease and observe the relationship between nurses' knowledge and their socio-demographic characteristics.

Methodology: The study was directed in isolation units of Al- Hussein teaching hospitals in Thi-Qar, Iraq for the period from June 1st,  2022 to November 27th, 2022. Non- probability (purposively) sample comprised 41 nurses. A questionnaire was used for data collection and it consists of two parts: the first part comprises socio demographic features, the second part includes self- administered questionnaire sheet wa

KE Sharquie, MM Al-Waiz, AA Noaimi, Iraqi Postgraduate Medical Journal, 2008 - Cited by 1