Danube University Krems

About: Danube University Krems is a education organization based out in Krems, Niederösterreich, Austria. It is known for research contribution in the topics: Stroke & Population. The organization has 498 authors who have published 1572 publications receiving 68797 citations.

Conceptual framework for establishing the African Stroke Organization

Abstract: Africa is the world’s most genetically diverse, second largest, and second most populous continent, with over one billion people distributed across 54 countries. With a 23% lifetime risk of stroke,...

Preventive effects of multiple domain interventions on lifestyle and risk factor changes in stroke survivors: Evidence from a two-year randomized trial.

Abstract: Background and aimBehavioral and lifestyle interventions in stroke patients need to be intense enough to result in sustainable treatment differences among groups of a randomized trial. Therefore, w...

Evaluating an InfoVis Technique Using Insight Reports

Abstract: The evaluation of Information Visualization (InfoVis) techniques can help to identify specific strengths and weaknesses of these methods. The following article describes the results of an empirical study assessing the contribution of an interactive InfoVis method based on a spring metaphor (GRAVI), exploratory data analysis (EDA) and machine learning (ML) to ease understanding. The application domain is the psychotherapeutic treatment of anorectic young women. The three methods are supposed to support the therapists in finding the variables which influence success or failure of the therapy. To conduct the evaluation we developed a report system which helped subjects to formulate and document in a self-directed manner the insights they gained when using the three methods. The results indicate that the three methods are complementary and should be used in conjunction.

Self-Organising Maps

Abstract: Highlights? FME as dialysis services global provider monitors patient satisfaction in its network. ? A specific questionnaire was developed and administered to the hemodialysis patients. ? To detect residual area of low satisfaction the Self-Organising Map was implemented. ? This method allows identifying niches of dissatisfaction for specific patient groups. Evaluation of patient satisfaction has become an important indicator for assessing health care quality. Fresenius Medical Care (FME) as a global provider of dialysis services through its NephroCare network has a strong interest in monitoring patient satisfaction.The aim of the paper is to test and validate a methodology for detecting a residual area of low satisfaction in dialysis patients.The FME Patient Satisfaction Programme questionnaire was distributed to haemodialysis (HD) patients treated in 335 centers of its network. It contained 79 questions covering various satisfaction aspects regarding Dialysis Unit, Dialysis Arrangement, Nurses, Doctors, etc.To analyse the data provided by the questionnaire, the Self-Organising Map (SOM) method was used. SOM is a neural network model for clustering and projecting high-dimensional data into a low-dimensional space, preserving topological relationships of original high-dimensional data spaces.10,632 HD patients completed the questionnaire. Mean age was 63.05?14.93years with 56.69% males. Response rate was 66%. Overall level of satisfaction was 1.99 (range from -3 to+3). On average patients were very satisfied with all issues. Nevertheless, a group of patients, around 60years old, balanced gender ratio, whose level of satisfaction was lower than 1, were highlighted.In the NephroCare clinics patient satisfaction with service is rather high. While traditional analysis usually stops here, the SOM method allows identification of areas of potential improvement for specific patient groups.