Objective: To measure the serum levels of Fetuin-A, ischemia-modified albumin (IMA), and ferritin in hospitalized patients with severe COVID-19in Baghdad, Iraq. Moreover, to determine these biomarkers' cut-off valuesthat differentiate between severely ill patients and control subjects. Methods: This case-control study was done from 15 September to the end of December 2021 and involved a review of the files and collectionof blood samples from patients (n=45, group1) hospitalized in COVID-19 treatment centersbecause of severe symptoms compared tohealthy subjects as controls (n=44, group2). Results: Fetuin-A serum levels were not statistically different between patients and controls. In contrast, IMA and ferritin levels were significantly different between the 2 groups, with patients' levelsbeing greater than control participants' (p 0.05). The critical values for the Fetuin-A, IMA, and ferritin tests were 393.78 mg/L, 59.22 ng/ml, and 126 µg/L, respectively, with concentration curves of 0.58, 0.70, and 0.93 for each. Conclusions: Patients and controls showed no significant difference in Fetuin-A levels in the blood. However, IMA and ferritin levels werehigher in people suffering from acute COVID-19 infection than in controls, with Fetuin-A values less than 393.78 mg/L andIMA and ferritin valueshigher than 59.22 ng/mland 126,000 μg/L, respectively.
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
... Show MoreThe proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.
In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete
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Background: Ulcerative colitis disease is a chronic inflammatory condition that affects the gastrointestinal tract. In regulation of this inflammatory process, Interleukin-6, C-reactive proteins and albumin have a major role. Overproduction of IL-6 by immunocompetent cells contributes to activate the liver to produce CRP, transudation of plasma albumin and development of the inflammatory condition. Elevated levels of IL-6 in saliva could be expected, because the saliva-producing cells are part of the digestive system. The purpose of this study was to assess salivary IL-6, CRP and albumin in ulcerative colitis patients in relation to oral findings. Materials and methods: Forty eight saliva specimens collected from three groups of subjects (s
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