Early detection burn-out risk for healthcare worker

Maria Peeters, involved in Future of Work research at Utrecht University has received funding for a team that will conduct AI-related research into burn-out in healthcare professionals. The funding comes from the EWUU knowledge alliance, in which the UU works together with TU/e, WUR and UMCU to tackle the challenges of our time. One of these challenges is health. 

Early detection burn-out risk for healthcare worker

Integrating psychological and physiological data in an AI-based framework

The project investigates the potential for an AI-based early warning system for burnout by analyzing both psychological and physiological data with conventional and machine learning techniques. The early detection system for burnout is the stepping stone towards timely strategies to prevent burnout development, thereby contributing to creating and maintaining a healthy and resilient workforce. The project uses the complementary expertise on psychological work-related factors that are related to burnout (UU), physiological person-related factors associated with burnout (TU/e), AI techniques and its application in the health domain (WUR), and developing, validating, evaluating, and implementing an AI Prediction Algorithm in the medical sector (UMC Utrecht).

Research team: Leander van der Meij (TU/e), Hubert Fonteijn (WUR), Maria Peeters (UU – Lead), Jaap Trappenburg (UMC Utrecht)