IdRis
PROJECT DURATION:
01/2022
—
06/2024
The Project
How can AI be used to improve medical care?
The treatment of older people is complex; individual illnesses and the accompanying multimorbidity must be taken into account. Geriatric assessments can be used to identify potential risks in order to make hospital stays safer, improve treatment success and reduce follow-up costs. However, these assessments are complex and require geriatric expertise and structured information. A new AI-based method should make it possible to identify potential risks at an early stage.
The project consortium is developing a method for the rapid, (partially) automated identification of risk potential in older people using digital biomarkers. This method should be available at various key points in healthcare in the future. Artificial intelligence (AI) methods will be used to identify potential risks such as frailty (frailty), delirium (acute confusion), dysphagia (difficulty swallowing) and a tendency to fall.
Our Role in the Project
HEALTH leitet das Projekt, insbesondere die Anforderungsanalyse (u.a. Co-Creation, Mockups und Prozessintegration) und das Datenmanagement und ist außerdem an der Entwicklung der KI-Modelle mittels Federated Learning und deren Evaluierung beteiligt.
Research groups
Downloads
Customer/Funding Organization
FFG
Project Partner
PH Predicting Health GmbH
Verein QiGG (Qualität in der Geriatrie und Gerontologie)
Kärntner Landeskrankenanstalten-Betriebsgesellschaft (KABEG)
Steiermärkische Krankenanstaltengesellschaft (KAGes)
Krankenhaus Göttlicher Heiland GmbH
Project Details
In order to identify potential risks at an early stage, we are working together with Predicting Health, Kärntner Landeskrankenanstalten-Betriebsgesellschaft (KABEG), Steiermärkische Krankenanstaltengesellschaft (KAGes) and Krankenhaus Göttlicher Heiland on an innovative approach to risk stratification. The aim of the project is to develop a digital method for the resource-saving, (partially) automated identification and prediction of risk potential in older people using digital biomarkers. This method should be available for widespread use in key areas of healthcare in the future. Artificial intelligence (AI) methods will be used to identify risks such as frailty (frailty), delirium (acute confusion), dysphagia (difficulty swallowing) and a tendency to fall.
The conception and development is carried out on an interdisciplinary basis together with future users as part of a co-creation process. This includes interdisciplinary focus groups and interviews, as well as process observations and workshops.
Project team
Philip
Stampfer
BSc
