Background: Coronavirus disease 2019 (COVID-19) is
one of the updated challenges facing the whole world.
Objective: To identify the characteristics risk factors that
present in humans to be more liable to get an infection
than others.
Methods: A cross-sectional study was conducted for
positively confirmed 35 patients with polymerase chain
reaction in Wasit province at AL-Zahraa Teaching
Hospital from the period of March 13th till April 20th. All
of them full a questionnaire regarded by risk factors and
other comorbidities. Data were analyzed by SPSS version
23 using frequency tables and percentage. For numerical
data, the median, and interquartile range (IQR) were used.
Differences between categoric

Vitamin K-dependent protein (VKDP) contributes to the development of lung cancer. The purpose of this research was to better understanding of the role of blood matrix Gla protein (MGP), VKDPs, Malondialdehyde (MDA), Superoxide dismutase (SOD) and Vitamin K (Vit K) in Iraqi patients with lung cancer before and after the first cycle of chemotherapy. Blood samples were collected from Al amal National Hospital for cancer treatment from October 2021 to May 2022, and a total of 80 samples were collected, divided into two groups (40 patient before taking a chemotherapy and 40 patients after taking chemotherapy), ranging in age from 20 to 45 years old. The results showed that although there were highly statistically significant differences in MD

Eriobotrya japonica Lindl., named as loquat, is a subtropical fruit tree of the family Rosaceae which is well known medical plant originated in  Japan and China. Loquat portions, like leaves, peels and fruits have been shown to possess various health usefulnesses.  In Chinese classical medicine, it is vastly utilized in many illnesses, like gastroenteric disorders, diabetes mellitus, pulmonary inflammatory diseases and chronic bronchitis. Loquat plant contain many active constituents, such as flavonoids, carotenoids, vitamins, polyphenolic compounds, other that have many biological effects like anti-tumor, anti-diabetic, anti-inflammatory, anti-mutagenic, antioxidant, antiviral, antitussive, hepatoprotective and hypoli

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

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