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Research

Our research is inspired by the challenges of changing environments. We develop methods for model learning, model adaption and change monitoring on streams. We work with timestamped data for applications in medicine and healthcare and for business. Next to analysing observational data, we also analyse experimental data and also conduct experiments on crowdworking.

Thematic Areas:

In the thematic area Medical Mining we develop mining methods for the analysis of cohort data from epidemiological and clinical studies, and of observational data from clinical databases and mHealth apps.

Together with the University Hospital Regensburg, the University Medicine Wuerzburg and the Charite we build phenotypes and predictive models for tinnitus patients and for tinnitus app users. More on our cooperations on tinnitus can be found here.

Together with the University Medicine of OVGU, we work on assessing immunfitness for senior people (see ImmunLearning) and on analysing experimental data for patients with diabetic foot syndrome.

Together with the University Hospital Regensburg, the University Ulm and further partners of the CHRODIS+ Joint Action, we analyse the data of pilot studies for the empowerment of patients with chronic diseases through mHealth apps. This work takes place as part of WP7 of the EU JOINT ACTION CHRODIS+, September 2017 - November 2020, Task 7.3 on pilots for the implementation of mHealth tools for fostering quality of care of patients with chronic diseases.

Together with the University Medicine Greifswald we work on learning classification models, on the identification of subpopulations with increased disease prevalence, on the characterization of such subpopulations, and on reducing the high-dimensional feature space in a semi- supervised way.

 

A detailed list of current and completed projects can be found on the reseach portal of Saxony-Anhalt, click here (in German).

Last Modification: 05.12.2020 - Contact Person:

Sie können eine Nachricht versenden an: Prof. Dr. Myra Spiliopoulou
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