Unlocking Data for Statistical Analyses and Data Mining: Generic Case Extraction of Clinical Items from i2b2 and tranSMART.

In medical science, modern IT concepts are increasingly important to gather new findings out of complex diseases. Data Warehouses (DWH) as central data repository systems play a key role by providing standardized, high-quality and secure medical data for effective analyses. However, DWHs in medicine must fulfil various requirements concerning data privacy and the ability to describe the complexity of (rare) disease phenomena.

An IT Architecture for Systems Medicine.

Systems medicine aims to support treatment of complex diseases like cancer by integrating all available data for the disease. To provide such a decision support in clinical practice, a suitable IT architecture is necessary. We suggest a generic architecture comprised of the following three layers: data representation, decision support, and user interface.

A framework for integrating heterogeneous clinical data for a disease area into a central data warehouse.

Structured collection of clinical facts is a common approach in clinical research. Especially in the analysis of rare diseases it is often necessary to aggregate study data from several sites in order to achieve a statistically significant cohort size. In this paper we describe a framework how to approach an integration of heterogeneous clinical data into a central register.

Alignment of high-throughput sequencing data inside in-memory databases.

In times of high-throughput DNA sequencing techniques, performance-capable analysis of DNA sequences is of high importance. Computer supported DNA analysis is still an intensive time-consuming task. In this paper we explore the potential of a new In-Memory database technology by using SAP's High Performance Analytic Appliance (HANA).