Protected Artificial Intelligence Innovation Environment for Patient Oriented Digital Health Solutions for developing, testing and evidence based evaluation of clinical value.

Developments in recent years, such as low-cost hardware for enormous computing power and machine learning techniques, have given AI new impetus in medicine as well, and in many medical application fields it is seen as a promising technology for disruptive advances, such as in disease diagnosis, personalized medicine, faster drug development, or even gene editing. However, one of the most essential prerequisites for delivering on this promise is the availability not only of Big Data, but of structured and high-quality data, as well as an environment in which new AI-based applications can be tested against a defined gold standard as a reference in a legally secure framework under real-world conditions. This topic is becoming increasingly relevant, especially against the backdrop of the new Digital Care Act.

The goal is therefore to automate the development of AI-based approaches (from the idea to translation into cross-site clinical routine). To this end, building on the Medical Data Integration Center (MeDIC) at Heidelberg University Hospital, an AI Innovation Center is to be established to build and test a pipeline for the development of AI-based applications.

The DFKI uses the infrastructure of the AI center to transfer an existing AI-based method for detecting diagnoses on image data to the domain of other image data using transfer learning methods. In the second part, DFKI is developing an algorithm that detects the patient’s position in the treatment pathway based on mostly unstructured text documents (information extraction) and image data from routine clinical documentation. This context-specific data is used to optimize diagnostics and therapy.


Universitätsklinikum Heidelberg

Deutsches Krebsforschungszentrum

Mint Medical GmbH


Bundesministerium für Gesundheit


Bundesministerium für Gesundheit

Publications about the project

Klaus Kades, Matthias A. Fink, Peter M. Full, Tim F. Weber, Jens Kleesiek, Michael Strube, Klaus Maier-Hein, Siting Liang

In: Tristan Naumann, Steven Bethard, Kirk Roberts, Anna Rumshisky (editor). Proceedings of the 4th Clinical Natural Language Processing Workshop. Clinical Natural Language Processing Workshop (ClinicalNLP-2022) located at NAACL 2022 July 14-14 Seattle WA United States Association for Computational Linguistics 7/2022.

To the publication
Siting Liang, Mareike Hartmann, Daniel Sonntag

In: 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics. NAACL Workshop on Bridging Human-Computer Interaction and Natural Language Processing (HCI+NLP-2022) located at NAACL 2022 October 15-July 15 Seattle, Washington United States Association for Computational Linguistics 7/2022.

To the publication

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz