336 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of AmsterdamNL35 papers
- Vrije Universiteit AmsterdamNL22 papers
- Amsterdam NeuroscienceNL12 papers
- University College LondonGB10 papers
- Delft University of TechnologyNL9 papers
- Leiden University Medical CenterNL9 papers
- Erasmus MCNL8 papers
- Radboud University NijmegenNL8 papers
- University Medical Center UtrechtNL8 papers
- Leiden UniversityNL7 papers
- Erasmus University RotterdamNL5 papers
- KU LeuvenBE5 papers
76 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…
SMART: A Flexible, Interpretable, and Scalable Spatio-temporal Brain Atlas from High-Resolution Imaging Data
John Kalkhof, Boris Gutman, Emile d'Angremont +2
We introduce SMART, a framework for learning a flexible, interpretable, and scalable spatio-temporal brain atlas from longitudinal high-resolution 3D medical images. Existing appro…
How does downsampling affect needle electromyography signals? A generalisable workflow for understanding downsampling effects on high-frequency time series
Mathieu Cherpitel, Janne Luijten, Thomas Bäck +3
Automated analysis of needle electromyography (nEMG) signals is emerging as a tool to support the detection of neuromuscular diseases (NMDs), yet the signals' high and heterogeneou…
BIOMERO 2.0: end-to-end FAIR infrastructure for bioimaging data import, analysis, and provenance
Torec T. Luik, Joost de Folter, Rodrigo Rosas-Bertolini +3
We present BIOMERO 2.0, a major evolution of the BIOMERO framework that transforms OMERO into a FAIR-compliant (findable, accessible, interoperable, and reusable), provenance-aware…
Robust Alignment of the Human Embryo in 3D Ultrasound using PCA and an Ensemble of Heuristic, Atlas-based and Learning-based Classifiers Evaluated on the Rotterdam Periconceptional Cohort
Nikolai Herrmann, Marcella C. Zijta, Stefan Klein +5
Standardized alignment of the embryo in three-dimensional (3D) ultrasound images aids prenatal growth monitoring by facilitating standard plane detection, improving visualization o…
MedPath: Multi-Domain Cross-Vocabulary Hierarchical Paths for Biomedical Entity Linking
Nishant Mishra, Wilker Aziz, Iacer Calixto
Progress in biomedical Named Entity Recognition (NER) and Entity Linking (EL) is currently hindered by a fragmented data landscape, a lack of resources for building explainable mod…
Federated Fine-tuning of SAM-Med3D for MRI-based Dementia Classification
Kaouther Mouheb, Marawan Elbatel, Janne Papma +8
While foundation models (FMs) offer strong potential for AI-based dementia diagnosis, their integration into federated learning (FL) systems remains underexplored. In this benchmar…
Horseshoe Forests for High-Dimensional Causal Survival Analysis
Tijn Jacobs, Wessel N. van Wieringen, Stéphanie L. van der Pas
We develop a Bayesian tree ensemble model to estimate heterogeneous treatment effects in censored survival data with high-dimensional covariates. Instead of imposing sparsity throu…
Inducing Causal Structure for Interpretable Neural Networks Applied to Glucose Prediction for T1DM Patients
Ana Esponera, Giovanni Cinà
Causal abstraction techniques such as Interchange Intervention Training (IIT) have been proposed to infuse neural network with expert knowledge encoded in causal models, but their…
False Discovery estimation in Record Linkage
Kayané Robach, Michel H. Hof, Mark A. van de Wiel
Integrating data from multiple sources expands research opportunities at low cost. However, due to different data collection processes and privacy constraints, unique identifiers a…
TrackRAD2025 challenge dataset: Real-time tumor tracking for MRI-guided radiotherapy
Yiling Wang, Elia Lombardo, Adrian Thummerer +25
Purpose: Magnetic resonance imaging (MRI) to visualize anatomical motion is becoming increasingly important when treating cancer patients with radiotherapy. Hybrid MRI-linear accel…
The 4D Human Embryonic Brain Atlas: spatiotemporal atlas generation for rapid anatomical changes
Wietske A. P. Bastiaansen, Melek Rousian, Anton H. J. Koning +4
Early brain development is crucial for lifelong neurodevelopmental health. However, current clinical practice offers limited knowledge of normal embryonic brain anatomy on ultrasou…
Parameter estimation in fluid flow models from undersampled frequency space data
Miriam Löcke, Pim van Ooij, Cristóbal Bertoglio
4D Flow MRI is the state of the art technique for measuring blood flow, and it provides valuable information for inverse problems in the cardiovascular system. However, 4D Flow MRI…
LLMs for Drug-Drug Interaction Prediction: A Comprehensive Comparison
Gabriele De Vito, Filomena Ferrucci, Athanasios Angelakis
The increasing volume of drug combinations in modern therapeutic regimens needs reliable methods for predicting drug-drug interactions (DDIs). While Large Language Models (LLMs) ha…
MyDigiTwin: A Privacy-Preserving Framework for Personalized Cardiovascular Risk Prediction and Scenario Exploration
Héctor Cadavid, Hyunho Mo, Bauke Arends +5
Cardiovascular disease (CVD) remains a leading cause of death, and primary prevention through personalized interventions is crucial. This paper introduces MyDigiTwin, a framework t…
Acquisition-Independent Deep Learning for Quantitative MRI Parameter Estimation using Neural Controlled Differential Equations
Daan Kuppens, Sebastiano Barbieri, Daisy van den Berg +4
Deep learning has proven to be a suitable alternative to least-squares (LSQ) fitting for parameter estimation in various quantitative MRI (QMRI) models. However, current deep learn…
Disease Progression Modelling and Stratification for detecting sub-trajectories in the natural history of pathologies: application to Parkinson's Disease trajectory modelling
Alessandro Viani, Boris A Gutman, Emile d'Angremont +1
Modelling the progression of Degenerative Diseases (DD) is essential for detection, prevention, and treatment, yet it remains challenging due to the heterogeneity in disease trajec…
MRI-based and metabolomics-based age scores act synergetically for mortality prediction shown by multi-cohort federated learning
Pedro Mateus, Swier Garst, Jing Yu +19
Biological age scores are an emerging tool to characterize aging by estimating chronological age based on physiological biomarkers. Various scores have shown associations with agin…
HELIOT: LLM-Based CDSS for Adverse Drug Reaction Management
Gabriele De Vito, Filomena Ferrucci, Athanasios Angelakis
Medication errors significantly threaten patient safety, leading to adverse drug events and substantial economic burdens on healthcare systems. Clinical Decision Support Systems (C…
AI in radiological imaging of soft-tissue and bone tumours: a systematic review evaluating against CLAIM and FUTURE-AI guidelines
Douwe J. Spaanderman, Matthew Marzetti, Xinyi Wan +13
Soft-tissue and bone tumours (STBT) are rare, diagnostically challenging lesions with variable clinical behaviours and treatment approaches. This systematic review provides an over…
Physics-informed graph neural networks for flow field estimation in carotid arteries
Julian Suk, Dieuwertje Alblas, Barbara A. Hutten +4
Hemodynamic quantities are valuable biomedical risk factors for cardiovascular pathology such as atherosclerosis. Non-invasive, in-vivo measurement of these quantities can only be…
A Flexible Model for Record Linkage
Kayané Robach, Stéphanie L van der Pas, Mark A van de Wiel +1
Combining data from various sources empowers researchers to explore innovative questions, for example those raised by conducting healthcare monitoring studies. However, the lack of…
Non-reciprocal breathing solitons
Jonas Veenstra, Oleksandr Gamayun, Martin Brandenbourger +4
Breathing solitons consist of a fast beating wave within a compact envelope of stable shape and velocity. They can propagate and carry information and energy in a variety of contex…
Analysis of cohort stepped wedge cluster-randomized trials with non-ignorable dropout via joint modeling
Alessandro Gasparini, Michael J. Crowther, Emiel O. Hoogendijk +2
Stepped wedge cluster-randomized trial (CRTs) designs randomize clusters of individuals to intervention sequences, ensuring that every cluster eventually transitions from a control…