Potential Supervisor: Daniel Fürstenau
Level: Master thesis

Background

The digitalization of nursing care opens up new opportunities for the prevention and reduction of falls through intelligent assistance systems. Current research shows that AI-based approaches can outperform conventional fall risk assessments, while at the same time placing high demands on data quality and data protection. Based on the findings of a three-year collaborative AI nursing care project at Charité, this thesis examines the development of a digital fall monitoring system and discusses whether a click dummy or a functional prototype should be considered an appropriate stage of development.

References

Nanevski I, Jäger S, Schulte-Althoff M, Behnke E, Fürstenau D, Biessmann F
The Potential of AI in Nursing Care: Multicenter Evaluation in Fall Risk Assessment
J Med Internet Res 2025;27:e71034
URL: https://www.jmir.org/2025/1/e71034
DOI: 10.2196/71034

Nanevski I, Mohebi M, Jäger S, Otte K, Schulte-Althoff M, Prasser F, Fürstenau D, Biessmann F
Evaluating the Quality of Synthetic Data in Health Care
Preprint; 2025
DOI: https://doi.org/10.21203/rs.3.rs-6320382/v1