AI Center for Health Care
Artificial intelligence is of critical relevance, especially in relation to health research. The goal of the U Bremen Research Alliance is therefore to create an “AI Center for Health Care” as a virtual institute for cooperation across the boundaries of the member institutions. Because of that and 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 University of Bremen and twelve federal and state-financed non-university research institutes from all German science organizations are working together in the U Bremen Research Alliance. The cooperation between researchers from various member institutions in the Alliance offers particular potential that is to be tapped. The goal of the U Bremen Research Alliance is therefore to create an “AI Center for Health Care” as a virtual institute for cooperation across the boundaries of the member institutions. This competence center should also be designed as an application hub in order to be able to quickly connect further partners from business and society in a rapidly developing field.
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 following research projects of the first application round receive funding:
AI surgery tracking is a joint project of the Fraunhofer Institute for Digital Medicine MEVIS and the University of Bremen. The project aims to help improve surgical care through robust and user-friendly AI-support systems.
The Intelligent Digital Guideline Editor (IDEAL) is a research project by Fraunhofer MEVIS, the Leibniz Institute for Prevention Research and Epidemiology - BIPS and the Applied Statistics group at the University of Bremen. The focus of the project 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 this project, the University of Bremen, Fraunhofer MEVIS and the German Research Center for Artificial Intelligence (DFKI) want to jointly develop a system that uses AI methods to improve the imaging for magnetic resonance tomographs.
Prof. Dr. Matthias Günther (University of Bremen)
The aim of this project by Fraunhofer MEVIS and the University of Bremen 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 is a joint project by Leibniz BIPS and Fraunhofer MEVIS. It 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.
Prof. Dr. Marvin N. Wright (Leibniz BIPS)