Hybrid AI system for delirium prediction to ease the burden on nursing practice

In hospital departments for surgical and internal medicine, acute but regressible cognitive impairment, so-called delirium, occurs in up to 50% of patients. Delirium leads to enormous stress in nursing practice. The care of patients with delirium is time-consuming and costly. However, delirium can be prevented if it is recognised in time and appropriate preventive measures are taken.

The aim of the KIDELIR project is to develop hybrid AI models for delirium prediction and to support reflective nursing decisions with the close involvement of nursing professionals.


  • Project duration -
  • Research theme Society, Health, Sustainability
  • Research Institute Care & Technology Lab

Project partners

  • Furtwangen University, Care & Technology Lab
  • University of Freiburg, Stabstelle Qualität und Entwicklung in der Pflege (Quality and Development in Nursing Unit), Neuromedical AI Lab, Centre for Geriatric Medicine and Gerontology, AI Ethics Lab, Institut für Digitalisierung in der Medizin (Institute for Digitalisation in Medicine), Datenintegrationszentrum (Data Integration Centre), Institute of Medical Biometry and Statistics
  • University of Freiburg, Department of Computer Science
  • Meona GmbH


The project is funded by the Federal Ministry of Education and Research (BMBF) within the framework of the Interactive Technologies for Health and Quality of Life research programme: "Miteinander durch Innovation" ("Together through Innovation").

[Translate to English:] KIDELIR (I32705-1)
[Translate to English:] KIDELIR (I32705-2)

Contact details