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Ethnographic research method for psychological and medical studies in light of COVID ‐19 pandemic outbreak: Theoretical approach
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Ethnographic research is perhaps the most common applicable type of qualitative research method in psychology and medicine. In ethnography studies, the researcher immerses himself in the environment of participants to understand the cultures, challenges, motivations, and topics that arise between them by investigating the environment directly. This type of research method can last for a few days to a few years because it involves in-depth monitoring and data collection based on these foundations. For this reason, the findings of the current study stimuli the researchers in psychology and medicine to conduct studies by applying ethnographic research method to investigate the common cultural patterns language, thinking, beliefs, and behavior for groups of addicts, the bullies and their bullies, hospitalized psychiatric patients, psychiatric nursing groups, psychologists, counselors and psychotherapists, elderly residents of care homes, abused persons, orphans, persons with special needs, groups of gifted students in gifted schools and centers, and family with special needs children. The ethnographic approach is a very important method in medicine to investigate the health case of the patients with chronic diseases, such as heart diseases, cancer, diabetes, blood pressure, and others. And examine the effectiveness of the treatment plan and take a decision to continue this plan, or change it, in the treatment of a particular disease group. As well as detection of the side effects of drugs and treatment plan for certain groups of patients, and learning about the common culture of pregnant women about the process of pregnancy and childbirth.

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in </p> ... Show More
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Publication Date
Sat Oct 31 2020
Journal Name
International Journal Of Intelligent Engineering And Systems
Automatic Computer Aided Diagnostic for COVID-19 Based on Chest X-Ray Image and Particle Swarm Intelligence
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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Theoretical and experimental studies for different compounds to calculate: electronic transfer, energy gap and NLO properties
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This work involves theoretical and experimental studies for seven compounds to calculate the electrons spectrum and NLO properties. The theoretical study is done by employing the Time Depending Density Functional Theory TD-DFT and B3LYP/high basis set 6-311++G (2d,2p), using Gaussian program 09. Experimental study by UV/VIS spectrophotometer device to prove the theoretical study. Theoretical and experimental results were applicable in spectrum and energy gap values, in addition to convergence theoretically the energy gap results from ΔEHOMO-LUMO and UV/VIS. spectrum. Consider the theoretical method very appropriate to compounds that absorb in vacuum UV.

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Effect of COVID-19 on the Role of Renin Enzyme and ACE2 and Hormones in PCOS Females
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Polycystic ovary syndrome (PCOS) is the most endocrine problem in women of regenerative age. PCOS women typically belong to an age and sex group which is at higher risk for severe coronavirus disease (COVID-19). COVID-19 targets cells through angiotensin-converting enzyme 2 (ACE2) receptor presents on cells in veins, lungs, heart, digestion tracts, and kidneys. Renin-Angiotensin System (RAS) over activity has likewise been described in metabolic disorders; type 2 diabetes mellitus (T2DM), and conditions shared by women with polycystic ovary condition. The point of this study is to know the job of renin and ACE2 in PCOS and coronavirus and its relationship with hormones and other metabolic parameters related. The study groups consist of 1

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Studying the Effect of COVID-19 on Liver Enzymes and Lipid Profile in Iraqi Recovering Patients
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  The Covid-19 virus disease has been shown to affect numerous organs and systems including the liver. The study aimed to compare lipid profiles and liver enzyme levels in individuals who had recovered from Covid-19 infection. To achieve the study objectives, liver Aspartate Aminotransferase (AST), Alanine Aminotransferase (ALT), Alkaline phosphatase (ALP),  Random Blood Sugar (RBS) and Lipid profile which include cholesterol, High-Density Lipoprotein (HDL), Triglycerides (T.G), Low-Density Lipoprotein (LDL), and Very low-density Lipoprotein (VLDL) were determined.

One hundred twenty serum samples were obtained, of which fifty samples were utilized as the control healthy persons (not affected by COVID) and seventy samples came f

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Publication Date
Sun Jan 01 2023
Journal Name
Rawal Medical Journal
Procalcitonin Level In COVID-19 Patients: A single center study
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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

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Publication Date
Thu Jun 01 2023
Journal Name
Ifip Advances In Information And Communication Technology
Rapid Thrombogenesis Prediction in Covid-19 Patients Using Machine Learning
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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

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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Docking Study of Naringin Binding with COVID-19 Main Protease Enzyme
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The Coronavirus Disease (COVID-19) has recently emerged as a human pathogen caused by SARS-CoV-2 virus was first reported from Wuhan, China, on 31 December 2019. Upon study, it has been used molecular docking to binding affinity between COVID-19 protease enzyme and flavonoids with evaluations based on docking scores calculated by AutoDock Vina. Results showed that naringin suppressed COVID-19 protease, as it has the highest binding value than other flavonoids including quercetin, hesperetin, garcina and naringenin. An important finding in this study is that naringin with neighboring poly hydroxyl groups can serve as inhibitors of COVID-19 protease bind to the S pocket of protein, it is shown that residues His163, Glu166, Asn142, His41and

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Publication Date
Mon Mar 28 2022
Journal Name
The Open Dentistry Journal
Depression, Anxiety and Stress Among Dentists During COVID-19 Lockdown
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Introduction:

The objective of this study was to investigate the levels of depression, anxiety, and stress among dentists during covid-19 lockdown and to investigate the relationship between stress and each mental health state.

Methods:

A cross-sectional survey on 269 dentists was conducted using DASS-21 and PHQ-9 questionnaires. Bivariate and multivariate models were constructed and the odds ratio (OR) was calculated to assess the strength of the association between an independent categorical variable and the outcome.

Results and Discussion:

Being unsatisfied with the job was as

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