Using Generic Meta-Data-Models for Clustering Medical Data

We present a generic, meta-model based data storage system for research, clinical studies or disease registers, which is enabled to store data of almost arbitrary structure. The system is highly costumizeable and allows the user to set up a professional web-based data acquisition system including administration area, data input forms, overview tables and statistics within hours. Furthermore, we evaluated a number of clustering algorithms regarding their ability to cluster the stored datasets for similarity search and further statistical analysis.