Data Science
Data Science is an interdisciplinary scientific field and deals with the extraction of knowledge from data. Using scientifically sound methods, processes, algorithms and systems, insights, patterns and conclusions are drawn from both structured and unstructured data.
Data Integration Centre
Click here to visit the websites of the DIZ. Magdeburg University Medicine’s Data Integration Center (DIZ) is concerned with the collation, conversion and secure provision of medical data from medical treatment for research purposes. This creates the conditions for inter-site data use processes between patient healthcare and medical research.
Scientific Computing
Contact: Prof. Dr. Dr. Johannes Bernarding
Scientific Computing consists of new methods of evaluating statistical data (multivariate methods), neurocomputing (MA Gupta) and the provision of deep learning modules for digital image processing (XNAT Link to DIZ/XNAT).
XNAT
- Open-source platform for secure archiving, processing and distribution of medical imaging data
- New: support for machine learning and AI-assisted annotation
- Provision and support in the context of MII und MIRACUM
Machine Learning
Provision of a framework for machine learning for medical image data based on Tensorflow
Cooperation partner MIRACUM
- Prof. Dr. Melanie Börries (University Hospital Freiburg)
- Prof. Dr. Rafael Mikolajczik (University Medicine Halle)
- Prof. Dr. Hans-Ulrich Prokosch (University Hospital Erlangen)