An Integrated AI Framework for Occupational Health: Predicting Burnout, Long COVID, and Extended Sick Leave in Healthcare Workers
We trained separate models for each occupational health risk but deployed them in a single, real-time web application. This integrated approach improves efficiency, enables multi-outcome workforce surveillance, and supports proactive interventions in healthcare settings.
Authors
- Maria Valentina Popa (ORCID: https://orcid.org/0000-0002-4062-1464)
- Lăcrămioara Ochiuz (ORCID: https://orcid.org/0000-0001-6447-0958)
- Călin Gheorghe Buzea (ORCID: https://orcid.org/0000-0003-2791-3400)
- Irina Luciana Gurzu (ORCID: https://orcid.org/0000-0003-3095-3497)
- Dragoș Ioan Rusu (ORCID: https://orcid.org/0000-0002-5485-0620)
- Bogdan Gurzu (ORCID: https://orcid.org/0000-0002-1834-9142)
- Letiția Doina Duceac (ORCID: https://orcid.org/0000-0002-1652-2618)
- Camer Salim
Institutions
- Ovidius University (RO)
- Grigore T. Popa University of Medicine and Pharmacy (RO)
- "Dunarea de Jos" University of Galati (RO)
- University of Bacău (RO)
- National Institute of Research and Development for Technical Physics (RO)
Publication Details
- Journal
- Healthcare
- Published
- 2025-09-10
- DOI
- https://doi.org/10.3390/healthcare13182266
- Citations
- 2
- Primary Topic
- Healthcare professionals’ stress and burnout
- Type
- article
- Field-Weighted Citation Impact
- 5.63