Aim: The assessment of the severity of acute pancreatitis (AP) is important for proper management of the disease and for its prognosis. The aim was to correlate clinical, biochemical, and imaging diagnostic parameters and evaluate their prognostic values in the early assessment of severity of AP. Materials and methods: We prospectively studied 128 consecutive patients with AP. The predictors were clinical, biochemical, and imaging diagnostic parameters. The outcome measure was the occurrence of complications. Abdominal sonogram, contrast-enhanced computer tomography, and pancreatitis-specific clinical and laboratory findings were done. Results: According to the Atlanta classification, 84 patients (65.6%) had mild and 44 (34.4%) had severe AP. The severity markers were significantly different between the mild and the severe groups (p < 0.001). Leukocyte count, serum albumin level, C-reactive protein (CRP), Ranson, acute physiology and chronic health evaluation II (APACHE II), and Glasgow score were the factors associated with radiological severity grade. Leukocyte count, CRP, Ranson score, APACHE II, and Glasgow score were the factors associated with the number and appearance of acute fluid collections (AFCs). A significant association was found between the number of AFCs and the occurrence of complications [odds ratio 4.4; 95% confidence interval 2.5-7.6]. Hospital stay was significantly longer in the group with severe disease as compared with the group with mild disease (p < 0.001). Conclusion: Clinical, biochemical, and imaging diagnostic parameters are related to the clinical course of AP and they can predict its severity. This allows us to determine the severity of the disease and to target the patients with high scores for close monitoring and more aggressive intervention. How to cite this article: Zerem D, Zerem O, Zerem E. Role of Clinical, Biochemical, and Imaging Parameters in predicting the Severity of Acute Pancreatitis. Euroasian J Hepato-Gastroenterol 2017;7(1):1-5.

Patients with cancer in developing and low-income countries have limited access to targeted cancer therapies. The transitional nature of these economieshas influencedhealthcare funding,whichhas resulted in the unavailability of targeted cancer treatments. Besides the three studies that will be described here, to our knowledge, no literature exists on the clinical outcome of patients treated with delayed targeted cancer therapy. To raise awareness on the importance of timely targeted cancer treatment, we will discuss three key issues: (1) the low number of targeted cancer therapies for different cancers, (2) thedelay incancer treatment, and (3) the unavailability of cancer diagnostics.

We propose a fast real-time state estimator based on the belief propagation algorithm for the power system state estimation. The proposed estimator is easy to distribute and parallelize, thus alleviating computational limitations and allowing for processing measurements in real time. The presented algorithm may run as a continuous process, with each new measurement being seamlessly processed by the distributed state estimator. In contrast to the matrix-based state estimation methods, the belief propagation approach is robust to ill-conditioned scenarios caused by significant differences between measurement variances, thus resulting in a solution that eliminates observability analysis. Using the DC model, we numerically demonstrate the performance of the state estimator in a realistic real-time system model with asynchronous measurements. We note that the extension to the AC state estimation is possible within the same framework.

The term "portfolio analysis", introduced in the economic theory by Harry Markowitz, is not a new term in scientific literature. However, analysis and criticism in the papers of local and foreign authors are mainly based on the examples of developed capital markets. There are very few cases of application of the portfolio analysis in the domestic capital market. The focus of this paper is on implementation of diversification of the bonds on the Banja Luka Stock Exchange. Using Markowitz's portfolio selection, we will prove that diversification, including all limitations, is possible and applicable onto the domestic bonds in the capital market.

Increased competition present in the higher education in BiH has conditioned the trend that institutions need to “fight” for each student through quality development at higher education institutions. This paper deals with means of enhancing quality at eMPIRICA College through continual investigation of students’ satisfaction. For the purpose of this research, we used a questionnaire with 26 statements on quality at the higher education institution, which were grouped in four quality dimensions using factor analysis. In addition, satisfaction and loyalty of students were measured where we compared students’ expectations and perceptions at the beginning and end of the academic year. Thus, a gap in the quality of education services at eMPIRICA was noted, as well as the gap in regards to satisfaction and loyalty. Using MANOVA it has been ascertained that there is a significant statistical difference between expected and perceived quality on the part of the students throughout all quality dimensions as well as in terms of students’ loyalty, and there is no significant statistical difference in satisfaction of students. Using ANOVA it has been deduced that with specific statements there are significant statistical differences in satisfaction and loyalty of students, while using t-test we observed a difference between arithmetic means of expected and perceived quality in all quality statements.

HCI researchers investigating the politics of technology design have recently focused on how design practice can tackle "Matters of Concern" - complex social issues perceived and experienced in multiple ways. These researchers suggest design research can generate new networks of human and non-human actors to express and act on these issues. Prior studies, however, tend to restrict their networks within traditional boundaries (e.g. existing organizations, local communities) and categories (e.g. human/nonhuman binary) without examining their significance for participants. We suggest collaborative map making as a reflexive method for understanding current Matters of Concern from the perspectives of diverse actors, not just researchers. As case studies of the method's use, we present two studies of domestic computing technologies in the US and South Korea, which show how collaborative map making allows salient networks to expand beyond the individual actors in the home to local and global power issues outside of boundaries (e.g. physical house) and categories (e.g. private/public space) commonly recognized in HCI. Our methodology provides HCI researchers with a way to understand existing Matters of Concern, so they can position themselves to address and act on these issues.