Bernhard Preim: Visual Analytics in Population Data


Medical data of populations are commonly acquired to analyze how often diseases
occur, how diseases are correlated (co-morbidity), and to identify risk factors. They are
complex, comprehensive, heterogenous with respect to data types, and often
incomplete. In addition, visual analytics methods to process such data have to consider
constraints, experiences, and preferences of epidemiologists who are the target user

We report on ongoing work that involves regression models, subspace clustering, and
heatmap visualization. These methods have in common that they try to emphasise
important relations. An interesting aspect of more recent population data, such as the
National Cohort, is that MR image data is also involved. This enables to analyze socio-
demographic data and data of medical tests along with shape descriptors that
characterise anatomical structure which is usually segmented from MRI data.

Thus, we would like to put forward a discussion of the possibilities offered by population
data and the mentioned visualisation techniques.

Organisational details

Visual Analytics in Population Data
Thursday, 25th August 2016
10:00 h

Biographic notes

[Translate to english:] Portrait Prof. Dr. Preims

Prof. Dr. Bernhard Preim became professor for visualisation at the faculty of computer sciences,  University Otto von Guericke, Magdeburg, Germany, in 2003. His resarch group at the Department of Simulation and Graphics has set its primary focus on algorithms and applications of medical visualisation. Preim is author and editor of multiple publications on fundamentals of interactive systems and medical visualisation.