Department of Social Sciences
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Browsing Department of Social Sciences by Author "Arbab, Ahmed Mohamed Hamad"
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Item Big data-based grey forecast mathematical model to evaluate the effect of Escherichia coli infection on patients with lupus nephritis(Elsevier B.V., 2021-07) Fan, Maoxiao; Gu, Shuaishuai; Jin, Yansheng; Ding, Lan; Ghonaem, Eman; Arbab, Ahmed Mohamed HamadThe grey predictive mathematical model based on big data was used for analysis on the effect of Escherichia coli infection on patients with lupus nephritis (LN) in this study. Then, 156 patients diagnosed with LN infections by Wuzhong People's Hospital's information system (HIS) from October 30, 2017 to October 30, 2019 were selected as the experimental group, and 89 patients without LN infections were selected as the control group. Besides, the grey theory mathematical model was applied to process the integrated data, and feature analysis was employed to screen out disease-related bio-markers for the diagnosis of LN. The two groups were compared for affected organs, treatment, laboratory indicators, pathogenic bacteria, and recovery status. Multivariate logistic regression was used to analyze the related factors of patients with infections. The results showed that the specificity, sensitivity, and accuracy of the big data diagnosis based on the grey theory mathematical model were 78.9%, 87.6%, and 92.1, respectively; hormones, c-reactive protein, procalcitonin, and the daily antibiotic dose were positively correlated with concurrent infections (P < 0.05); 38 cases of Gram-negative bacteria were screened out, accounting for the largest proportion (37.18%); the effective rate of the experimental group was obviously lower than that of the control group (P < 0.05), suggesting that C-reactive protein (CRP), procalcitonin (PCT), antibiotics, daily dose of hormones, and serum albumin were independent risk factors for LN infection. In conclusion, the grey predictive mathematical model based on big data had high specificity, sensitivity, and accuracy in diagnosing the occurrence of infection in patients with LN; LN infection was mainly respiratory infection, and gram-negative bacteria were the main pathogen. Patients with LN infections showed higher serum creatinine, 24-hour urine protein quantification, CRP, and PCT, and lower serum albumin and recovery effect versus those without LN infections. © 2021 The Author(s)Item Correlation between HPV infection and ovarian epithelial cancer diagnosed by Dynamic Contrast-enhanced magnetic resonance imaging information technology under exponential distribution mathematical model(Elsevier B.V., 2021-07) Liang, Bo; He, Han; Zeng, Lingyu; Pan, Min; Huang, Tingting; Wang, Xinmin; Kabene, Stefane Mostefa; Arbab, Ahmed Mohamed HamadThis research aims to analyze the correlation between human papillomavirus (HPV) infection and ovarian epithelial cancer based on exponential distribution mathematical model, so as to provide an experimental basis for the early diagnosis of ovarian epithelial cancer by magnetic resonance imaging (MRI) in the future. In this study, 124 patients with ovarian epithelial cancer tissues pathologically confirmed in our hospital from March 31, 2017 to February 20, 2019 were selected as the experimental group, and 64 patients with normal ovarian tissues were selected as the control group, and the positive rate of HPV infection was detected by the computer cell test (CCT) system. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was constructed and adopted to analyze the scanning images. The correlation between HPV infection and pathological type, clinical stage, tissue differentiation degree, and CA125 in serum was studied by exponential distribution mathematical model. The results showed that the positive rate of HPV infection in the ovarian tissues of the experimental group was significantly higher than that of the control group (P < 0.05). Highly differentiated patients accounted for 25.97%, moderately differentiated patients accounted for 43.81%, and lowly differentiated patients accounted for 30.22%. Patients with clinical stage I-II accounted for 24.72%, patients with stage III accounted for 49.11%, and patients with stage IV accounted for 26.17%. HPV infection was significantly correlated with clinical stage III and moderate tissue differentiation by MRI of patients (P < 0.05), and extremely significantly correlated with clinical stage IV and low tissue differentiation by MRI (P < 0.001). The above findings show that the information technology of dynamic contrast-enhanced magnetic resonance imaging can clearly display the lesion metastasis of ovarian epithelial cancer patients with high soft tissue resolution. © 2021 The Author(s)