Analysis, modeling, and simulation of emergency department

Overcrowding in the Emergency Department (ED) is one of the most important issues in healthcare systems. Two major causes of this congestion are identified, the first one is unjustified Emergency Department visits and the second one a lack of downstream beds. The lack of downstream beds can deteriorate the quality of care for patients who need hospitalization after an ED visit. In this paper a generic simulation model is developed in order to analyse patient pathways from the ED to hospital discharge

TOPOLOGICAL DATA ANALYSIS AS A TOOL FOR CLASSIFICATION OF DIGITAL IMAGES

Topological data analysis, as a branch of applied mathematics, is one of the newer areas that enable data analysis. The basic tool of this field is persistent homology, the main method of topological data analysis and it is used to process the data set in this article. Persistent homology is a method that detects the topological features of a space reconstructed from a data set. The application is illustrated on simple synthetic generated sets. In this article, we proposed and evaluated a new model that includes topological features into the classification process in real data sets composed of digital images. We got results in which there are some improvements in most of the statistical values for the classification performance over a model that does not include these topological features

Analysis, modeling, and simulation of emergency department

Overcrowding in the Emergency Department (ED) is one of the most important issues in healthcare systems. Two major causes of this congestion are identified, the first one is unjustified Emergency Department visits and the second one a lack of downstream beds. The lack of downstream beds can deteriorate the quality of care for patients who need hospitalization after an ED visit. In this paper a generic simulation model is developed in order to analyse patient pathways from the ED to hospital discharge

Analysis and Visualization of Social Networks

The huge development of social networks opens the need for their analysis. The visualization of social networks is an important and powerful tool for such kind of analysis. There are many software packages which can be used for visualization. In this paper we are using graph theory, Python, and the free software Gephi to make visualization of social networks. Particularly we have made visualization of social network Twitter in order to show the relations between its users. This visualization helps in the analysis of relations and interactions between social media users