Establishing the AI Center for Health Care addresses as one of the activities in the lead project Artificial Intelligence the critical relevance of artificial intelligence in relation to health research. The intention aims at the cooperation of the member institutions and in particular at funding PhD students working in interdisciplinary projects. The objective is to establish a virtual institute across the boundaries of the member institutions.
In order to promote the growth of joint research projects in the field of AI and health care, the U Bremen Research Alliance tendered the funding of cooperative research projects in 2021 for the first time. The funds are provided by the State of Bremen and awarded through the U Bremen Research Alliance.
The AI Center for Health Care comprises the following nine projects:
The focus of the project IDEAL is the development of a methodology to use causal inference and adaptive statistical procedures to simplify the planning of efficient clinical studies and to be able to quickly integrate their results into existing guidelines using a digital guideline editor.
In the project On the way to AI-assisted intelligent magnetic resonance imaging the project partners want to jointly develop a system that uses AI methods to improve the imaging for magnetic resonance tomographs.
The aim of the project NAKO+ILSE is to merge multimodal data from various studies in order to improve the prediction of the biological, immunological and cognitive age of individuals and to support the early detection of dementia.
NAKO-MNA aims at the AI-based development of a multimodal implicit data model based on combined image data and complex tabular data from the NAKO health study. One application goal is the improved ability to sensitively detect deviations from the norm and previously undiscovered incidental findings.
In the project PORTAL the project partners jointly work on AI-based methods to optimize laser additive manufacturing for endoprotheses. A forward-model shall predict the properties of the implant with respect to its field of application. Furthermore, a backward-model shall help to find optimized parameter settings for the manufacturing process based on predefined specifications of the implant.
Speakers of the lead project Artificial Intelligence
Prof. Dr.-Ing. Horst Hahn, Fraunhofer Institute for Digital Medicine MEVIS
Prof. Dr. Frank Kirchner, German Research Center for Artificial Intelligence
Prof. Dr.-Ing. Tanja Schultz, University of Bremen
Coordinator of the lead project Artificial Intelligence
Dr. Monika Michaelis, U Bremen Research Alliance