Background :Infectious disorders in general have high morbidity and mortality.. CNS infections include many disorders like bacterial meningitis, tuberculous and other subacute and chronic meningitis, viral meningitis, cerebral abscess, spinal cord infections, and others.
Objective: To assess our locality about prevalence of CNS infections , to have more awareness regarding CNS infections, and to try to find the proper way to reduce their prevalence and to treat them in appropriate way.
Method :We revised the records of all the cases of CNS infections excluding cases of spinal cord infections who were admitted in the wards of neuroscience hospital over the previous two years ( from July/2010 to June 2012 ),those were 132 cases.Seaso

Background: Squamous cell carcinoma (SCC) is the most prevalent malignant neoplasm of the oral cavity that exhibits certain histological variations. Verrucous carcinoma (VC) is an uncommon exophytic low-grade well-differentiated variant of SCC. Cellular differentiation and morphology play important roles in cell functions and maintenance of structural integrity .As the cancer is a malignant process in which disorder of the cell growth and behavior occurs, such changes may differ in different tumor types and within different grades of the same tumor. Materials and Methods:Forty two formalin – fixed, paraffin – embedded tissue blocks were included in this study (30 blocks were diagnosed as OSCC and 12 blocks were diagnosed as OV

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

This booklet contains the basic data and graphs forCOVID-19 in Iraq during the first three months of thepandemic ( 24 February to 19 May - 2020 ) , It isperformed to help researchers regarding this health problem (PDF) Information Booklet COVID-19 Graphs For Iraq First 3 Months. Available from: https://www.researchgate.net/publication/341655944_Information_Booklet_COVID-19_Graphs_For_Iraq_First_3_Months#fullTextFileContent [accessed Oct 26 2024].

Background: The COVID-19 infection is a more recent pandemic disease all over the world and studying the pulmonary findings on survivors of this disease has lately commenced.

Objective: We aimed to estimate the cumulative percentage of whole radiological resolution after 3 months from recovery and to define the residual chest CT findings and exploring the relevant affecting factors.

Subjects and Methods: Patients who had been previously diagnosed with COVID-19 pneumonia confirmed by RT-PCR test and had radiological evidence of pulmonary involvement by Chest CT during the acute illness were included in the present study. The radiol

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

 This study attempts to address the importance of communicative digitization in the field of various arts for the sake of continuity of shopping and aesthetic, artistic and intellectual appreciation of artistic achievements by the recipient on various places of their residence in light of the COVID 19 crisis, and to highlight the importance of the plastic arts of the Iraqi painter exclusively and how it expresses in a contemporary way the environment or life reality in Iraq in light of this crisis. With all its implications affecting the life reality from various aspects and methods of its negative and positive employment. As for the research procedures, the researcher reviewed the research methodology represented by the descriptive ana

ABSTRACT Objective: Cardiovascular diseases are the first ranked cause of death worldwide. Adhering to health promoting lifestyle behaviors will maintain an individual’s cardiovascular health and decrease the risk of cardiovascular diseases. Methods: In this descriptive study, 150 nursing faculty were surveyed via a non-probability (purposive) sampling method to assess their adherence to health promoting lifestyle in order to know the risk of cardiovascular diseases. The Arabic version of Health-Promoting Lifestyle Profile II (HPLP-II) was used to achieve this goal. Results: Seventy-two nursing faculty completed the survey. The results indicated that the study sample had moderate level of health promotion based on Health-Promot