Publikation
Exacerbation Risk and Quality of Life Prediction for Chronic Obstructive Pulmonary Disease Patients with Complex Chronic Conditions
Jakob Fabian Lehmann; Gesa Wimberg; Serge Autexier; Agni Delvinioti; Giulio Pagliari
In: Proceedings of the IEEE EMBC 2025. International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC-2025), 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, July 14-17, Kopenhagen, Denmark, IEEE, 2025.
Zusammenfassung
Machine learning modeling using clinical data has
emerged as an important research topic in recent years. Many
stakeholders could benefit from drawing meaningful insights
from patient data by means of support for the clinical personnel
in disease management and for patients in coping with their
disease. This work presents a machine learning framework
for the prediction of exacerbation events and quality of life
related scores. The underlying dataset contains clinical and self-
reported real-world data from patients with chronic obstructive
pulmonary disease. The resulting machine learning models
have a reliable performance while model explanations provide
interesting clinical conclusions