Medical Mining for Epidemiology and Clinical Research

Medical mining is a broad research area, where mining methods are applied to solve problems of diagnostics and treatment, as well as for the understanding of disease progression. Medical mining encompasses learning on hospital records (for decision support in diagnosis and treatment), and learning on epidemiological data:

Data Mining in Epidemiological Studies:
We cooperate with the Institute of Community Medicine, University Medicine Greifswald, on the identification of risk factors and predictive factors for hepatic steatosis. In this cooperation, we study longitudinal data from the cohorts SHIP and SHIP-TREND (Study of Health in Pomerania). We develop methods for learning on high-dimensional, timestamped, multi-relational data. We address challenges of object dissimilarity, data skew and of missing information (due to changes in the recording protocol).
Within the Faculty of Computer Science, we work together with the Visualization Lab (Bernhard Preim) on medical mining and visual analytics for the analysis of the population studies' data of Univ Greifswald. Our joint emphasis is on building easily interpretable patterns.

Data Mining in Diabetology Research:
Together with the Diabetology clinic of the University of Magdeburg, we work on the analysis of plantar pressure and temperature patterns for patients with diabetic foot syndrome and we investigate the potential of intelligent wearables.

Cooperation with VisLab:
We cooperate with the Visualization Lab of the Faculty of Computer Science on the rupture status classification of intracranial aneurysms, using angiographic images. We develop methods for an automated rupture status assessment from feature extraction, to classification with subsequent feature ranking & inspection in order to identify the most important morphological and hemodynamic features.