در هنگام جستجو کلمه در قسمت عنوان میتوانید کلمات مورد جستجو را با کاراکتر (-) جدا کنید.
کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Iranian Journal of Neonatology
- نوع مقاله: Journal Article
- کلمات کلیدی: skin,Injury,neonate,NICU,Related Factors
- چکیده:
- چکیده انگلیسی: Background: Skin is the most important defense mechanism of the neonate's body. The admission to the Neonatal Intensive Care Unit (NICU) is a risk factor for neonatal skin injuries. Therefore, to prevent these complications, it is essential to identify the risk factors. The present study aimed to investigate the incidence of skin injuries and its related factors in neonates admitted to the NICU.
Methods: This cohort study was conducted in two NICUs in one perinatal hospital in Tehran, Iran, from January 2018 to June 2018. The sampling was performed using the census method. The data were collected through a demographic characteristics form, a risk factor assessment checklist, and the European Pressure Ulcer Advisory Panel (EPUAP) tool. The data were analyzed in SPSS software (version 19) through Fisher's exact test and chi-square test.
Results: Out of 368 neonates, 126 cases had skin injuries, and the others were healthy. The mean values of weight and age of the neonates with skin injuries were 796.68±1606.82 g and 5.18±30.82 days, which was significantly lower than those of the infants without skin injury (p <0.05). The results of the risk factors analysis also showed that the second-grade injuries were the most frequent. Moreover, the drug leakage (14.2%, n=33) and nasal continuous positive airway pressure (12.06%, n=28) had the highest prevalence. The results of the effect of risk factors on the wound grade also showed that drug leakage, diaper rash, and surgical injuries had a significant effect on the wound grade.
Conclusion: The results showed that in addition to neonatal conditions, equipment, and neonatal care play a significant role in the incidence of skin injuries. Skin is the most important defense barrier of the neonate's body and it is vitally important to take care of it. Therefore, it is necessary to identify and prevent such injuries.
- انتشار مقاله: 05-10-1398
- نویسندگان: Maryam Javaheri Abkenar,Leila Khanali Mojen,Fateme Shakeri,Maryam Varzeshnejad
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Mathematical Finance and Application
- نوع مقاله: Journal Article
- کلمات کلیدی: Artificial Neural Network,financial crisis,Genetic Algorithm
- چکیده:
- چکیده انگلیسی: Organizations expose to financial risk that can lead to bankruptcy and loss of business is increased nowadays. This may leads to discontinuity in operations, increased legal fees, administrative costs and other indirect costs. Accordingly, the purpose of this study was to predict the financial crisis of Tehran Stock Exchange using neural network and genetic algorithm. This research is descriptive and practical and in order to collect data Stock Exchange database software has been used. For data analysis, we used artificial neural network in base form and artificial neural network mix with genetic algorithm. In addition for methods comparison, determination coefficient, Mean squared error and Root-mean square error have been used. The result of study shows that the best artificial neural network is a network with a hidden layer and eight neurons in the layer. This network could predict 97.7 percent of healthy and bankrupt companies correctly for test data. Furthermore the best mixed neural network with genetic algorithm is a network with 400 replications and population size 50, one layer and eight neurons which could correctly predict 100% of healthy and bankrupt companies. Finally, comparison of results of two methods shows that the best method for predicting financial crisis is mixed neural network with genetic algorithm.
- انتشار مقاله: 14-12-1397
- نویسندگان: Nader Rezaei,Maryam Javaheri
- مشاهده