818 citations
- Erasmus University RotterdamNL40 papers
- Delft University of TechnologyNL32 papers
- University of CopenhagenDK21 papers
- Eindhoven University of TechnologyNL14 papers
- Erasmus MC Cancer InstituteNL13 papers
- Amsterdam University Medical CentersNL8 papers
- Harvard UniversityUS8 papers
- Leiden University Medical CenterNL8 papers
- University of AmsterdamNL8 papers
- Radboud University Medical CenterNL7 papers
- Radboud University NijmegenNL7 papers
- University College LondonGB7 papers
130 papers
Towards Trustworthy AI for Glioma Diagnosis: A Task-Aware Evaluation of Uncertainty Quantification
Gonzalo Esteban Mosquera Rojas, Sebastian R. van der Voort, Carolin M. Pirkl +3
Uncertainty Quantification (UQ) is a key requirement for trustworthy AI in high-stakes medical image analysis. In this work, we evaluate UQ in a multi-task Deep Learning framework…
Automatic Extraction of Structured Information from Brain MRI Reports Using an Open-Weight Large Language Model
Kaouther Mouheb, Amos Pomp, Antoine Manenti +9
Objectives: Automatic data extraction from free-text radiology reports enables large-scale research, but few studies assessed the performance of large language models (LLMs) on Dut…
Handling Overtime Constraints in Mixed Integer Linear Programming for Surgical Scheduling: A Comparison of Neural Network and Classical Linearization Techniques
Cindy Pistorius, J. Theresia van Essen
Uncertainty in surgery durations continues to be difficult to account for in operating room scheduling. In particular, it remains complex to accurately incorporate uncertainty in s…
Disease Progression and Subtype Modeling for Combined Discrete and Continuous Input Data
Sterre de Jonge, Elisabeth J. Vinke, Meike W. Vernooij +3
Disease progression modeling provides a robust framework to identify long-term disease trajectories from short-term biomarker data. It is a valuable tool to gain a deeper understan…
Therapist-Robot-Patient Physical Interaction is Worth a Thousand Words: Enabling Intuitive Therapist Guidance via Remote Haptic Control
Beatrice Luciani, Alex van den Berg, Matti Lang +2
Robotic systems can enhance the amount and repeatability of physically guided motor training. Yet their real-world adoption is limited, partly due to non-intuitive trainer/therapis…
q3-MuPa: Quick, Quiet, Quantitative Multi-Parametric MRI using Physics-Informed Diffusion Models
Shishuai Wang, Florian Wiesinger, Noemi Sgambelluri +4
The 3D fast silent multi-parametric mapping sequence with zero echo time (MuPa-ZTE) is a novel quantitative MRI (qMRI) acquisition that enables nearly silent scanning by using a 3D…