Background: Quality of life in brain tumor patients is an emerging issue and has prompted neurosurgeons to recon¬sider the need for cognitive assessment in the course of treatment. To date there has been a lack of comprehensive neuropsychological assessment performed preoperatively and in the acute postoperative period in our hospitals.Objectives: to establish the effects of tumors and their surgical treatment, from a neuropsychological perspective, on cognitive functioning in patients with cerebral Gliomas. Methods: This is a prospective study conducted in the Neurosurgical Hospital in Baghdad, Iraq, during the period from January 1999 to January 2001. Any patient admitted during the period of the study with clinical history, signs, sy

COVID-19 is a unique viral infectious illness that causes a variety of symptoms and health hazards, particularly to the respiratory system and has been declared a worldwide pandemic. The disease is characterized by a cytokine release in severe conditions. Interleukin-6 (IL-6), a proinflammatory cytokine, mediates an important immunomodulatory process. Also, vitamin D was identified to have a role in the innate immunity of individuals. Our study was designed to find the role of IL-6 and vitamin D in COVID-19 patients, as well as, to see whether there is a link between vitamin D deficiency and cytokine syndrome development. The study included 90 COVID-19 patients and 30 control people from Baghdad, Iraq. The age of the participants was non-s

In this study the prevalence of acute, sub-acute and chronic toxoplasmosis were monitored in a group of Iraqi pregnant women according to the anti-T.gondii antibodies (IgG and IgM), as well as the levels of both progesterone and estrogen hormones were measured using mini-VIDAS®technique. This study demonstrated that there was high prevalence of chronic toxoplasmosis (31.70%) when it compared with acute and sub-acute type, results also showed that the acute toxoplasmosis always related with low concentration of both progesterone and estrogen which were (5.35 ± 7.15 ng/ml) and (70.66 ± 51.08 pg/ml) respectively

Acute myeloid leukemia is a malignant disease results from mutation in a multipotent haemopoietic stemcell. The study aimed to investigate NPM1 and FLT3-ITD mutations in Iraqi patients with AML and correlateresults with other clinical and laboratory findings. Fifty-eight AML patients, admitted to Baghdad TeachingHospital from October 2019 till March 2020 in addition to 25 normal controls, were included in the study.A detailed history, laboratory investigations including FLT3-ITD and NPM1 mutations were collected fromand analyzed. FLT3-ITD was detected in 17.24% of patients, NPM1 mutation in 10.34%. Most of thepatients are presented with pallor. FLT3-ITD mutation had a higher blast cell count (74%) while NPM1mutation had higher WBCs

<span>Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynami

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti