Objective: The study the association of procalcitonin (PCT) and c-reactive protein (CRP) levels in COVID-19 patients and it's role as a guide in progress and management of those patients. Methodology: This cross-sectional study analyzed 200 CIOVID-19 patients in a single privet center in Baghdad, Iraq from January 1, 2021 to January 1, 2022. Demographic data like age, sex, and clinical symptoms were recorded. High sensitivity CRP and PCT in the serum were measured via dry fluorescence immunoassay (Lansionbio-China). Results: Out of 200 patients, 50 had moderate Covid and 150 had severe disease. Mean serum PCT levels was 0.039±0.05 ng/mL in the moderate group (range 0.011-0.067) and 0.43±0.21 ng/mL in the severe group (range 0.21

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

Abstract

This research aims to identify the challenges faced by families of children with intellectual disabilities and to identify the impact of the challenges facing them on the mental health of their children with intellectual disabilities. Based on the following questions: What is the nature of the challenges faced by families of children with disabilities and how do these challenges affect the mental health of their children with intellectual disabilities? The study was conducted on a sample of four families of six children with intellectual disabilities, depending on the degree and type of disability. To achieve the study's objectives, the qualitative approach was used, Because of the importance of accessin

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

Abstract: Plastic pollution is a major issue of the current century. This waste is found in seas, freshwater, lakes, rivers, coastal areas, and soil. In this article, this article discusses the various sources of plastic pollution, including the manufacturing process of plastics and the addition of materials to improve their properties, as well as the use of single-use plastics that are not recyclable, in addition to burning and illegal waste disposal in the open. The impact on public health is through human exposure to toxins from plastics in the environment directly through inhaling dust and fumes, consuming contaminated food and drink, and skin contact. Indirectly, when marine creatures consume microplastics, they will find their way

This paper addresses the nature of Spatial Data Infrastructure (SDI), considered as one of the most important concepts to ensure effective functioning in a modern society. It comprises a set of continually developing methods and procedures providing the geospatial base supporting a country’s governmental, environmental, economic, and social activities. In general, the SDI framework consists of the integration of various elements including standards, policies, networks, data, and end users and application areas. The transformation of previously paper-based map data into a digital format, the emergence of GIS, and the Internet and a host of online applications (e.g., environmental impact analysis, navigation, applications of VGI dat

Objectives:  The present study aimed to assess the compulsion among health care providers during the pandemic of COVID-19.

Methodology:  a descriptive design was used in the present study.  This study was conducted from October 10th, 2020 through May 20th, 2021.  The study was conducted on a probability (convenient) sample of 248 physicians and nurses who work at Baghdad Teaching hospital in Baghdad city.  The instrument was used in this study is the COVID Stress Scale-Arabic version (CSS).

 Results:  The result of this study showed that 42 % of HCPs had moderate symptoms and 36% of them had mild compulsive symptoms, and