ABSTRACT
The aim of this study was to determine the immune function of human leukocyte antigens and some vital indicators in Covid 19 patients. This study was conducted at Ibn Al-Khatib hospital, Baghdad. Sixty four blood sample of Covid 19 patients (32 male and 32 female patients), while healthy volunteers group 15 male and 15 female with age between 10 to 60. Level of IL-1b, CD4, WBC, ESR, Urea, sugar test, were measured results showed a significant increase (P<0.01) in each measured of IL-1b, CD4, WBC, ESR, Urea, Sugar. The more infection of Covid 19 with some factors such as, smoking, chronic diseases. The measurement of the level of IL-1b, CD4 by means of the enzyme - linked immunosorbent assay (ELISA), and WBC, PLT, measurement method using ABX micros 60 hematology analyzer, Urea, Sugar semi-automated chemistry analyzer using Mindray BC-5000. The data was analyzed with Graph pad prism software. © 2023 Author(s).
ABSTRACT
Corona pandemic showed how artificial intelligence has become a part of our daily lives and is breaking into all fields at a high rate and in different ways. Relying on the conventional techniques to test patients such as RT -PCR has two major drawbacks;a long time to get results and a lack of test kits. Therefore, data mining with machine learning techniques has been suggested to investigate covid-19. In this work, chest x-ray image-based covid-19 detection approach is proposed. Three types of x-ray images Covid-19, Pneumonia, and Normal, are used in two frameworks: image visualization and image segmentation. First, the x-ray samples are visualized using histograms to analyze the pixel-value distributions. The visualization approach helps covid-19 specialists to discover the intensity level of infection by examining the corresponding histograms. Second, a segmentation approach is developed with a k-mean algorithm to provide extra image tuning for infected areas. Three different centroids are used to provide different tuning granularity levels. The suggested frameworks give a fast and reliable methodology to help physicians to decide whether there is a virus or not in the x-ray sample. This is done statistically by histograms and visually by monitoring the segmented infected areas. © 2021 IEEE.