Zeitschrift für Gesundheit und medizinische Informatik

Aiming to study the local functional structure of brain function network in resting state, the Fuzzy C-means (FCM) algorithm is adapted to modular the brain functional network. Then the nodes in module are connected into a network using correlation between the time series extracted from Functional Magnetic Resonance Imaging (fMRI) data. Afterwards node degree, clustering coefficient and shortest path length are used to analyse the functional characteristics of networks. Finally, the differences in activation between patients and normal controls’ brain regions are compared through Amplitude of Low Frequency Fluctuation (ALFF). Experimental results demonstrate that, the shortest path length of the patient is smaller than that of the normal human, so the information transmission rate increases. Clustering coefficient is higher than the normal, and the degree of grouping of network is enhanced. The correlation between the patient nodes is generally greater than the normal, and there is a weakened situation in the local area. It also found that the proportion of region for the activation level higher than the average of the whole brain in normal with more than the patient. In particular, the activation level of the Precentral gyrus (PreCG) and other regions in patient has a large degree decline. And the activation level in left Caudate nucleus (CAU.L), the lenticular nucleus, Putamen (PUT) and the lenticular nucleus, Palladium (PAL) and other regions is increased for patient. The research results verify the feasibility of modularization analysis of brain functional network using algorithm and correlation in resting state.

Introduction: Social network is systematic means of assessing formation and informal networks by mapping and analysing relationships among people, groups, and units of work group or even entire organizations. In this article information Sharing and problem solving methods of health extension worker in Konso woreda was assessed. Objective: This study is aimed to assess information sharing using social network analysis among health extension workers in Konso woreda. Methods: A cross-sectional survey was conducted on all health extension workers in Konso woreda in Southern Ethiopia, using pretested structured pretested roster type questionnaire. All analysis performed by UCINET. Results: The response was rate 77(93%). For who know who network: Degree (64.8), Betweenness (11.1), Eigenvector (0.11), density (79.28%), and for information sharing network Degree (22.3), Betweenness (54.6), Eigenvector (0.11), density (27.2%). Using MR-QAP indicated significant variables such as experience (B=-0.041, p=0.0085), media (B=-0.0430, p=0.0055), site (B=-0.11, p=0.0005) and who know who B=0.1722, p=0.0005). People share information have positive performance (B=0.0466, p=0.01450) Conclusion: The information sharing in HEWs was inadequate. Sharing was observed among different sites rather than the same, people of different experiences than that of the same, and people who have different knowledge of Medias for information Sharing but for who know each other and have performance.

Background: Angiography, as the gold standard for the diagnosis of coronary artery disease, has made an attempt to predict coronary artery disease by comparing the efficiency of gene expression programming, as a new data mining technique, and artificial neural network, as a conventional technique. Besides, the study went further to present the results of feature selection based on stepwise backward elimination, classification and regression tree. Methods: The subjects were assessed for nine coronary artery disease risk factors to develop a prediction model for the disease. They included 13,288 patients who were chosen to undergo angiography for the diagnosis of coronary artery disease; from this sample, 4059 subjects were free from the disease while 9169 were suffering from it. Modeling was carried out based on gene expression programming and artificial neural network techniques. The Delong’s test was then used to choose the final model based on the area under the Receiver Operating Characteristic (ROC) curve. Results: The model, developed based on artificial neural network, had AUC of 0.719, accuracy of 73.39%, sensitivity of 93.44% and specificity of 28.34%. On the other hand, the model, formulated based on gene expression programming, had AUC of 0.720, accuracy of 73.94%, sensitivity of 93.29% and specificity of 31.43%. Delong’s test showed no significant difference between the two models (p value=0/789). Then, feature selection method was used to choose a model with four risk factors and an accuracy rate of 73.26%. Conclusion: Comparison of the results showed no significant difference between the two modeling techniques. The gene expression programming model was very easy to present and interpret; it could also be easily converted to other programming languages; so, with these features in mind, the researchers preferred to choose this technique.

E-Learning methods have shown a great number of advantages compared to traditional lectures and classroom settings. These include lower total cost, an increased temporal and spatial flexibility as well as taking individual interests and learning style preferences into account. We present a newly implemented case-based E-Learning program at the Vienna Medical University (MUV) for medical students. With over 110 interactive cases, in which learning objectives are aligned with two thirds of the MUVs medical curriculum. In future we aim to examine possible quantitative differences in exam grades and an improvement in knowledge or skills after using E-Learning versus using traditional methods.

Community participation in medico-legal form bench-mark of health determinants and quality integrated services towards criminal justice support in health. Globally, over 44 million cases of unclaimed bodies or missing dead persons (UCBOMDPs) occur annually, 88% of these cases are in Sub Saharan Africa. In western Kenya and Kenya the rate of UCBOMDPs from road traffic accidents accounts 30% and 10% respectively, 80% of these UCBOMDPs are associated with limited community participation/next of kins in identification of UCBOMDPs, thus prevailing chronic prevalence of occupational health and safety hazards in public mortuaries. The study aimed to assess extent of community participation, uptake of community mortuary services and awareness on quality medico-legal concepts, training, embalming and assess how of knowledge, attitude and practices (KAP) of service providers influence the uptake of medico-legal concepts to mitigate occupational health and safety hazards and improve health. In Exploratory and cross sectional, 235 respondents were investigated through purposive and saturated sampling using structured questionnaires, focus group discussions (FGDs), observations and key informant interviews (KII) guides to collect data. Analysed statistical inferences and contents analysis to saturation, results showed, 94% of mortuary service providers in tier 4 were primary and secondary education drop outs of males, on contract jobs with limited access to quality forensic in mortuary science, contrarily to trained females and males counterparts from tiers 5 and 6 mortuary facilities on permanent. Embalming by gravitation method significant OD (1.2, 0.44). Prevalence of male being admitted as UCBOMDPs in the community was significant with, OD (8.3, 0.12), RR (0.33), 95% CI (1.23, 1.02), significance were associated with male deliberately leaving IDs in houses for anonymity. Community participation in medico-legal concepts were sufficient than Detective police with OD (0.43, 6.0), 95% CI (2.12, 1.34). Advocacy to empower community comprehensively and holistically in medico-legal concepts remains vital.

Background: Obesity and its co-morbidities are characterized by a chronic low-grade in amatory state, uncontrolled expression of metabolic measurements and dis-regulation of various forms of stress response. However, the contribution and correlation of in ammation, metabolism and stress responses to the disease are not fully elucidated. In this paper a cross-sectional case study was conducted on clinical data comprising 117 human male and female subjects with and without Type 2 Diabetes (T2D). Characteristics such as anthropometric, clinical and biochemical measurements were collected. Methods: Association of these variables with T2D and BMI were assessed using penalized hierarchical linear and logistic regression. In particular, elastic net, hdi and glinternet were used as regularization models to distinguish between cases and controls. Differential network analysis using closed-form approach was performed to identify pairwise-interaction of variables that influence prediction of the phenotype. Results: For the 117 participants, physical variables such as PBF, HDL and TBW had absolute coefficients 0.75, 0.65 and 0.34 using the glinternet approach, biochemical variables such as MIP, ROS and RANTES were identified as determinants of obesity with some interaction between inflammatory markers such as IL-4, IL-6, MIP, CSF, Eotaxin and ROS. Diabetes was associated with a significant increase in Thiobarbituric Acid Reactive Substances (TBARS) which are considered as an index of endogenous lipid peroxidation and an increase in two inflammatory markers, MIP-1 and RANTES. Furthermore, we obtained 13 pairwise effects. The pairwise effects include pairs from and within physical, clinical and biochemical features, in particular metabolic, inflammatory, and oxidative stress markers. Conclusion: We showcase those markers of oxidative stress (derived from lipid peroxidation) such as MIP-1 and RANTES participate in the pathogenesis of diseases such as diabetes and obesity in the Arab population.

Increasing diversified world, era of international power diffusion and regionalisation as the world muddles through travel and trade to climate change requires promoting a more cohesive global regime to ameliorate the deficiencies in local and global 2013-2015 and 2015-2016 Ebola and Zika virus epidemics public health emergency of international concern respectively. Zika epidemics devastating and complex complications exposed the flaws in the global surveillance architecture to deal with cross-border health pandemics prevention and containment. This paper examines trade-off between technology-based data access and dissemination, Zika virus (ZIKV) epidemics complications and digital implications in care delivery solutions in pre-, during and post epidemics response and rebuilding. Our findings showed that IT-based health informatics and mobile applications are evolving and minimum global standards to open access and sharing of relevant epidemics data and information on risk communication. Public awareness and alertness, health promotion and education, counselling and guidelines on integrated syndrome surveillance and response were the most common goals and objectives during viral epidemics reduce and avert further transmission. The uses in healthcare services delivery, management, and planning was also documented and have played a critical role in raising awareness EVD and ZIKV travel restriction and delay pregnancy to women at reproductive age, effective use of personal protective equipment and cultural practices against EVD and ZIKV infections spread. Importantly, IT-based enhanced frontline improved collaborative data sharing and communication, coordinated response and recovery. The efficiency of IT-based data and information sharing and communication practices is of critical benefits for evidence informed early warning, social mobilization, advocacy, monitoring and evaluation capabilities. Mobile-based applications innovations during Zika and Ebola epidemics were very crucial for better evidence-based local and global preparedness and solutions to prevent and control epidemics impacts, promote shared benefits and economic growth.

The hierarchical medical care system reform in China may lead to drastic changes of medical care utilizations distribution in different medical care subsystems. A medical care system dynamics model was constructed to simulate the intervention scenarios according to the reform measures, and to estimate changes of demands, utilizations distribution and reasonable resources allocation, in order to provide optimized intervention for decision-makers.

Introduction: Females genital mutilation/Cutting is a harmful traditional procedure disturbing the health of girls and women. It has a continuing sexual, physiological and psychological influence on women health life. The objective of current study was to visualize and analyze the global scientific activities in the field of female genital mutilation/Cutting during a period of 15 years through 2001-2015. Methodology: A Scientometric analysis was carried out to depict the global activities towards scientific production in the field of female genital mutilation/cutting during a period of 15 years. The Core Collection of Web of Science database was employed to extract all papers indexed as a topic of female genital mutilation/cutting through 2001-2015. The Science of Science Tool was used to map the co-authorship network of papers in the field. Results: Analysis of data showed that, although the number of papers in the field of female genital mutilation/cutting was not remarkable, but it steady increased through the period of study, so that the number of papers in 2015 was two times greater than those in 2006. English consisting 94% of total publication was the language of publications. The vast majority of publication type was in the form of journal articles (65%). Based on the Bradford Scatterings law the journal of “International of Gynecology Obstetrics” was the most productive journal. USA, England and Australia were the most productive countries in the field. Conclusion: The study concluded that the research activities in the field of FGM/C regarding to the number of circumcised women in the world was very small and insufficient. The psychological aspects of FGM/C have been neglected by the scientists as well as the women health organizations.