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 systematic literature review demonstrates that ML-powered tools can alleviate the burden on healthcare systems. These tools can analyze significant amounts of medical data and potentially improve predictive and preventive healthcare.
That achieve a level of excellence for the quality of university education cannot be achieved only by uniting the efforts of all employees at the university and active participation by students and by alumni and the labor market and society, however we can say that the administrative and academic university staff play an active role and the largest in achieving equivalent quality of higher education, It should unite the efforts of all employees in the educational institution in order to achieve quality education. It is the concept of quality of education, quality assurance and overall management of the quality of the basic pillars on which it is based university education. That highlight the need fo
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Binary logistic regression model used in data classification and it is the strongest most flexible tool in study cases variable response binary when compared to linear regression. In this research, some classic methods were used to estimate parameters binary logistic regression model, included the maximum likelihood method, minimum chi-square method, weighted least squares, with bayes estimation , to choose the best method of estimation by default values to estimate parameters according two different models of general linear regression models ,and different s
... Show MoreThe aim of this paper is to derive a posteriori error estimates for semilinear parabolic interface problems. More specifically, optimal order a posteriori error analysis in the - norm for semidiscrete semilinear parabolic interface problems is derived by using elliptic reconstruction technique introduced by Makridakis and Nochetto in (2003). A key idea for this technique is the use of error estimators derived for elliptic interface problems to obtain parabolic estimators that are of optimal order in space and time.
Abstract:
We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.
In this research, I estimate the reliability function of cluster function by using the seemingly unrelate
... Show MoreA simulation study is used to examine the robustness of some estimators on a multiple linear regression model with problems of multicollinearity and non-normal errors, the Ordinary least Squares (LS) ,Ridge Regression, Ridge Least Absolute Value (RLAV), Weighted Ridge (WRID), MM and a robust ridge regression estimator MM estimator, which denoted as RMM this is the modification of the Ridge regression by incorporating robust MM estimator . finialy, we show that RMM is the best among the other estimators
Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental
... Show MoreA field experiment was conducted during the autumn of 2021 at the Agricultural Research Department station / Abu Ghraib to evaluate the soil moisture, water potential distribution, and growth factors of maize crops under alternating and constant partial drip irrigation methods. In the experiment, two irrigation systems were used, surface drip irrigation (DI) and subsurface irrigation (SD); under each irrigation system, five irrigation methods were: conventional irrigation (CI), and 75 and 50% of the amount of water of CI of each of the alternating partial irrigation APRI75 and APRI50 and the constant partial irrigation FPRI75 and FPRI50 respectively. The results showed that the water depth for conventional irrigation (C1) was 658.3
... Show MoreCefixime is an antibiotic useful for treating a variety ofmicroorganism infections. In the present work, tworapid, specific, inexpensive and nontoxic methods wereproposed for cefixime determination. Area under curvespectrophotometric and HPLC methods were depictedfor the micro quantification of Cefixime in highly pureand local market formulation. The area under curve(first technique) used in calculation of the cefiximepeak using a UV-visible spectrophotometer.The HPLC (2nd technique) was depended on thepurification of Cefixime by a C18 separating column250mm (length of column) × 4.6 mm (diameter)andusing methanol 50% (organic modifier) and deionizedwater 50% as a mobile phase. The isocratic flow withrate of 1 mL/min was applied, the temper
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