Browsing by Author "Muwafak, Bishr Muhamed"
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Item Establishment of differential model of recovery treatment for children with minor brain injury and mental disorder syndrome(American Institute of Mathematical Sciences, 2021) Zhang, Wei; Ma, Ai; Takshe, Aseel; Muwafak, Bishr MuhamedThe paper established a differential equation model for 194 children with ADHD in outpatient clinics from September 2019 to August 2020 and compiled a children's clinical diagnostic interview scale based on the fourth edition of the American Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). The CDIS standard divides it into three phenotypes: attention deficit predominant (ADHD-I), hyperactivity-impulsive predominance (ADHD-HI) and mixed (ADHD-C). The results of the study showed that the distribution of subtypes in the study cases: ADHD-I accounted for 45.9% (89 cases), ADHD-HI accounted for 7.7% (15 cases), ADHD-C accounted for 46.4% (90 cases); ADHD-C: ADHD-I is 1:1. CDIS scale total score: 194 cases of attention deficit symptoms were (7.2 ± 1.4) points, and hyperactivity-impulsive symptoms were (5.4 ± 2.2) points. The frequency of attention deficit symptoms in 194 cases was (79.5 ± 2.9) %, and the frequency of hyperactivity-impulsive symptoms was (59.8 ± 3.5) %. Therefore, it can be concluded that DSM-IV defines three phenotypes in this sample. The proportion of ADHD-HI is low, and the proportion of ADHD-I and ADHD-C is similar; age influences the phenotype distribution. ©2021 the Author(s), licensee AIMS Press.Item The ZigBee wireless information medical monitoring for bacterial infections using filter mathematical model(Elsevier B.V., 2021-06) Cao, Maocheng; Wang, Junjing; Wu, Chunfeng; Takshe, Aseel A.; Muwafak, Bishr Muhamedthe study drew attention to the application of ZigBee wireless sensor network system based on digital filter mathematical model in the post-chemotherapy monitoring of hematological tumor patients, and the diagnostic value of the average fluorescence intensity of peripheral blood neutrophil CD64 (nCD64) for bacterial infections. In this study, 128 patients with hematological tumors who underwent chemotherapy in hospital were selected as the research subjects. The ZigBee wireless sensor network system based on digital filtering mathematical model was used to monitor the physiological indicators of patients in real time. The subjects were divided into the infected group and the non-infected group according to clinical characteristics and imaging examination results, and dynamic monitoring was performed on patients of long hospital stay but without fever. The two groups were compared for the average fluorescence intensity of neutrophils and the expression of C-reactive protein (CRP), and the ROC curve (Receiver Operating Characteristic Curve) was used to judge the cut-off value, sensitivity, and specificity of PCT, CRP, and nCD64. It was found that, under the ZigBee wireless sensor network system based on digital filtering mathematical model, the patient's ECG frequency of the mixed baseline drift was relatively low, and the system filtered through the 0.5 Hz sine shock chill superposition. The detection accuracy was high; the subgroups of the infection group (the increased group, the normal group, the decreased group, and the deficient group) showed higher nCD64 average fluorescence intensity versus the non-infection group (P < 0.05). Dynamic monitoring points 1 and 3 showed higher nCD64 average fluorescence intensity versus the control group, non-infection group, and dynamic monitoring point 2 (P < 0.05).The ROC curve revealed that the sensitivity and specificity of average fluorescence intensity of nCD64 (in the infection group and the dynamic monitoring group) were 90.4 and 86.7, 79.6 and 79.6, respectively, in the diagnosis of hematological tumor patients after chemotherapy, higher than PCT and CRP. It suggested that ZigBee wireless information medical monitoring based on digital filter mathematical model can effectively diagnose bacterial infections in patients with hematological tumors after chemotherapy, together with nCD64 average fluorescence intensity. © 2021 The Author(s)