Explainable artificial intelligence is increasingly used in machine learning (ML) based decision-making systems in healthcare. However, little research has compared the utility of different explanation methods in guiding healthcare experts for …
To make predictions and explore large datasets, healthcare is increasingly applying advanced algorithms of artificial intelligence. However, to make well-considered and trustworthy decisions, healthcare professionals require ways to gain insights in …
Improving interpretability and performance of risk prediction models for decision support in clinical environments
Main host institution: KU Leuven
Supervisor: Katrien Verbert (Informatics Section, KU Leuven)
Foreign host institution: University of Maribor