Abstract

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 group.

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.

Organizational Details

Visual Analytics in Population Data

Date: Thursday, 25th August 2016
Time: 10:00 am
Room: O27/331