Clinical Data Warehouse - Projects

Personalized medicines is a major focus of our current research. Besides extensive lab work, we also focus on structured and high-quality data collection in the clinical routine. Annotation of experimentally analyzed samples with a clinical context can offer a broader understanding of a patient’s precise condition and treatment options.

Our data warehouse aims to be the central interface for researchers to obtain data from a multitude of different systems within the clinical ecosystem ranging from general systems like the Clinical Information System (CIS) to specific purpose-build software like our medi-frAIme system allowing for structured data collection within the clinical routine.

Additionally, we also make it possible to reference and re-use previously collected data points and samples.

In terms of data analysis we focus on longitudinal data to develop clinical decision support systems helping with risk assessment, therapy stratification and prediction of serious medical complications. Besides the regularly gathered clinical information, we continuously monitor patients with wearable devices and incorporate this data modality into machine learning models to gain a better understanding of early markers for complication. A major milestone will be to preemptively inform the patient about adverse events and reduce the time to treatment in those cases.

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