Browsing Faculty of Communication, Arts and Sciences by Author "Abo Keir, Mohammed Yousuf"
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ItemPDCA cycle theory based avoidance of nursing staff intravenous drug bacterial infection using degree quantitative evaluation model(Elsevier B.V., 2021-07) Jiang, Lina ; Sun, Xiaofeng ; Kabene, Stefane Mostefa ; Abo Keir, Mohammed YousufThe purpose is to explore the positive role of PDCA (Plan, Do, Check, Act) cycle theory in the hospital information management system to avoid intravenous drug bacterial infection of nursing staff based 360-degree quantitative evaluation model. The research focus is to promote the rational application of intravenous drugs among nursing staff, and the application data of intravenous drug among nursing staff under the same background and different management schemes are selected as the research objects, which are divided into the PDCA cycle theory pre-intervention group and post-intervention group. Through the statistical comparison of the error data of medical advice and nursing work, the role of PDCA circulation theory intervention in promoting the rational application of intravenous drugs in nursing staff is analyzed. The work performance of nursing staff is managed through the application of 360-degree quantitative evaluation model. The results show that after the one-year PDCA cycle theoretical intervention, both the number of unreasonable medical advice and the rate of unreasonable medical advice show a decreasing trend, the rate of correction of medical advice of nursing staff increases from 54.5% to 87.8%, the overall incidence of nursing errors significantly decreases, and the difference is statistically significant (P < 0.05). Among them, nursing errors mainly referred to the situation of intravenous drug bacterial infection. Meanwhile, it is found that after the intervention of PDCA cycle theory, the working time of each link of nursing staff is significantly shortened and the working efficiency is significantly improved. The introduction of 360-degree evaluation thinking and quantitative evaluation theory and the construction of 360-degree quantitative evaluation model can evaluate the nursing performance scientifically. © 2021 The Author(s)
ItemRelationship between helicobacter pylori infection and type 2 diabetes using machine learning BPNN mathematical model under community information management(Elsevier B.V., 2021-07) Ma, Huan ; Xiao, Juan ; Chen, Zhaoxu ; Tang, Dong ; Gao, Yuqiang ; Zhan, Shuhui ; Ghonaem, Eman ; Abo Keir, Mohammed YousufObjective: This exploration aims to explore the effect of Helicobacter pylori infection on blood glucose mechanism and gastric function in patients with type 2 diabetes under the background of electronic medicine, and the effect of community information management platform on health management efficiency of patients with Helicobacter pylori, so as to lay the foundation for clinical research on Helicobacter pylori participation in the mechanism of type 2 diabetes. Methods: In this paper, 300 patients who were treated in our hospital from June 2016 to June 2019 were selected as the research object. Among them, 228 patients with type 2 diabetes were recorded as the experimental group, and 72 patients with non-type 2 diabetes were recorded as the control group. 13C breath test and serum IgG antibody test were performed on each research object. Patients infected with Helicobacter pylori in the experimental group were divided into groups according to the degree of urine albumin excretion. Urinary albumin excretion rate was <30 mg/24 h as group A, between [30,300]mg/24 h as group B, and greater than 300 mg/24 h as group C. The control group was recorded as group D. Blood biochemical indexes and gastroscopy were detected in the four groups; the blood biochemical indexes of each group were compared and analyzed by statistical software; the artificial intelligence health information platform in community information management was established, and the mathematical prediction model of diabetes was established based on Back Propagation Neural Network (BPNN). Results: The proportion of Helicobacter pylori infection in patients with type 2 diabetes was 60%, and the proportion of Helicobacter pylori infection in the control group was 40%. There was a significant difference in fasting blood glucose indicator and cholesterol indicator between group C and group D, P < 0.05. There was a significant difference in the percentage indicator of glycated protein between group A and group C, P < 0.05. There was a significant difference in normal gastroscopy between group A and group D, P < 0.05. In the process of training, the error of the train set of the mathematical model based on BPNN is gradually reduced, and it has good convergence. When the number of hidden layer units is 3, the AUC (Area Under Curve) of train set is the largest. When the number of hidden layer units is 1, the AUC of the test set is the largest, so the network model with one hidden layer unit is selected. Conclusion: The community use efficiency of each performance of the artificial intelligence health information platform in community information management has been significantly improved compared with that before optimization, which can improve the health management level on the basis of patients' electronic medical information. © 2021 The Author(s)