Visual Analytics in Public Health

Applicant:

Prof. Dr.-Ing. Bernhard Preim, Magdeburg
Otto-von-Guericke-Universität Magdeburg
Institut für Simulation und Graphik
Magdeburg

Prof. Dr.-Ing. Klaus-Dietz Tönnies, Magdeburg
Otto-von-Guericke-Universität Magdeburg
Institut für Simulation und Graphik
Magdeburg

Prof. Dr. Henry Völzke, Greifswald
Universitätsklinikum der Ernst-Moritz-Arndt-Universität Greifswald
Institut für Community Medicine
Abt. Methoden der Community Medicine
Greifswald

Project:

Visual Analytics in Public Health (Publications)

Summary:

Research in Public Health generates a huge amount of heterogeneous data characterizing the lifestyle and health status of people from questionnaires and clinical measurements. At the University of Greifswald, a long-term study is carried out for epidemiological studies and for investigation of prevalence and type of normal and pathological variation. Data acquisition comprises image and non-image data from approximately 9000 subjects. Among these data are also dynamic medical image data which were investigated in the first stage of the SPP project. To fully exploit the potential of these data in preventive medicine, sophisticated analysis and exploration techniques are necessary.
Since the range of possible analysis questions is large and at present unknown to its full extent, analysis must be flexible, efficient and intuitive to enable repeatability over a long period of time. Furthermore, visual analytics must include part of the feature generation instead of analyzing the feature space.
Procedures will be developed for visualizing and analyzing data from medical image and nonimage data as well as from demographical data. The methods shall scale well with respect to different research questions on different subsets of the same data pool, since this is the usual scenario if researchers from different clinical disciplines pursue their projects. We will extend tools developed in the previous grant period to analyze patterns in the population as opposed to individual patterns of pathology. We will involve the user at an early stage of analysis including the generation of features which is usually part of the preprocessing.