Coronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing different MCDM approaches has been raised based on different perspectives; however, the latest one, namely, the fuzzy decision by opinion score method that was produced in 2020, has efficiently been able to solve some existing issues that other methods could not manage to solve. because of the multiple criteria decision-making problem and because some criteria have a conflict problem. The methodology of this research was divided into two main stages. The first stage related to identifying the decision matrix used eight different ML methods on chest X-ray (CXR) images and extracted a new decision matrix so as to assess the ML methods. The second stage related to FDOSM was utilized to solve the multiple criteria decision-making problems. The results of this research are as follows: (1) The individual benchmarking results of three decision makers are nearly identical; however, among all the used ML methods, neural networks (NN) achieved the best results. (2) The results of the benchmarking group are comparable, and the neural network machine learning method is the best among the used methods. (3) The final rank is more logical and closest to the decision-makers' opinion. (4) Significant differences among groups' scores are shown by our validation results, which indicate the authenticity of our results. Finally, this research presents many benefits, especially for hospitals and medical clinics, with a view to speeding up the diagnosis of patients suffering from COVID-19 using the best machine learning method.
This research deals with a shrinking method concernes with the principal components similar to that one which used in the multiple regression “Least Absolute Shrinkage and Selection: LASS”. The goal here is to make an uncorrelated linear combinations from only a subset of explanatory variables that may have a multicollinearity problem instead taking the whole number say, (K) of them. This shrinkage will force some coefficients to equal zero, after making some restriction on them by some "tuning parameter" say, (t) which balances the bias and variance amount from side, and doesn't exceed the acceptable percent explained variance of these components. This had been shown by MSE criterion in the regression case and the percent explained v
... Show MoreElectrical Discharge Machining (EDM) is a widespread Nontraditional Machining (NTM) processes for manufacturing of a complicated geometry or very hard metals parts that are difficult to machine by traditional machining operations. Electrical discharge machining is a material removal (MR) process characterized by using electrical discharge erosion. This paper discusses the optimal parameters of EDM on high-speed steel (HSS) AISI M2 as a workpiece using copper and brass as an electrode. The input parameters used for experimental work are current (10, 24 and 42 A), pulse on time (100, 150 and 200 µs), and pulse off time (4, 12 and 25 µs) that have effect on the material removal rate (MRR), electrode wear rate (EWR) and wear ratio (WR). A
... Show MoreNano gamma alumina was prepared by double hydrolysis process using aluminum nitrate nano hydrate and sodium aluminate as an aluminum source, hydroxyle poly acid and CTAB (cetyltrimethylammonium bromide) as templates. Different crystallization temperatures (120, 140, 160, and 180) 0C and calcinations temperatures (500, 550, 600, and 650) 0C were applied. All the batches were prepared at PH equals to 9. XRD diffraction technique and infrared Fourier transform spectroscopy were used to investigate the phase formation and the optical properties of the nano gamma alumina. N2 adsorption-desorption (BET) was used to measure the surface area and pore volume of the prepared nano alumina, the particle size and the
... Show MoreThis study is unique in this field. It represents a mix of three branches of technology: photometry, spectroscopy, and image processing. The work treats the image by treating each pixel in the image based on its color, where the color means a specific wavelength on the RGB line; therefore, any image will have many wavelengths from all its pixels. The results of the study are specific and identify the elements on the nucleus’s surface of a comet, not only the details but also their mapping on the nucleus. The work considered 12 elements in two comets (Temple 1 and 67P/Churyumoy-Gerasimenko). The elements have strong emission lines in the visible range, which were recognized by our MATLAB program in the treatment of the image. The percen
... Show MoreBackground: In December 2019, an episode of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARSCoV2) was reported in Wuhan, China and has spread around the world, increasing the number of contagions. Cytomegalovirus (CMV) and Epstein-Barr virus (EBV) are common herpesviruses that can cause persistent latent infections and affect the developing immune system.The study was conducted to explore the prevalence and reactivation of CMV and EBV antibodies in COVID-19 patients group in comparison to healthy group and to investigate the association between the presence of these viruses with each of severity of disease and oral hygiene. Materials and Methods: Eighty Five subjects were participated in this case control study (5
... Show MoreCompelling evidence proved that coronavirus disease (COVID-19) disproportionately affects minorities. The goal of the present study was to explore the effects of intersected discrimination and discrimination types on COVID-19, mental health, and cognition. A sample of 542 Iraqis, 55.7% females, age ranged from 18 to 73, with (M = 31.16, SD = 9.77). 48.7% were Muslims, and 51.3% were Christians (N = 278). We used measures for COVID-19 stressors, executive functions, intersected discrimination (gender discrimination, social groups-based discrimination, sexual orientation discrimination, and genocidal discrimination), posttraumatic stress disorder (PTSD), depression, anxiety, status and death, existential anxieties, and health. We conducted in
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The prevalence of gastrointestinal symptoms of COVID-19 is variable with different types of presentations. Some of them many present with manifestations mimicking surgical emergencies. Yet, the pathophysiology of acute abdomen in the context of COVID-19 remains unclear. We present a case of a previously healthy child who presented with acute appendicitis with multisystemic inflammatory syndrome. We also highlight the necessity of considering the gastrointestinal symptoms of COVID-19 infection in pediatric patients in order to avoid misdiagnosis and further complications. |
BACKGROUND: Vaccine hesitancy and reluctant had an important obstacle in achieving protection and population immunity against coronavirus disease 19 (COVID-19). It is essential to achieve high COVID-19 vaccination acceptance rates among medical students and health care workers to provide recommendations and counseling vaccine hesitant population. AIM: This study aims to identify level of COVID-19 hesitancy, attitude, knowledge, and factors that affect vaccination decision. MATERIALS AND METHODS: A cross-sectional study was done among medical students in Al-Kindy College of Medicine, University of Baghdad, Baghdad, Iraq. Data collection was done through an online Google Forms questionnaire during 2021 from 810 medical students.
... Show MoreSUMMARY. The objectives of the present study were to assess the possible predictors of COVID-19 severity and duration of hospitalization and to identify the possible correlation between patient parameters, disease severity and duration of hospitalization. The study included retrospective medical record extraction of previous coron avirus COVID-19 patients in Basra hospitals, Iraq from March 1st and May 31st, 2020. The information of the participants was investigated anonymously. All the patients’ characteristics, treatments, vital signs and laboratory tests (hematological, renal and liver function tests) were collected. The analysis was conducted using the SPSS (version 22, USA). Spearman correlation was used to measure the relations
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