most citedPhysics-informed graph neural networks for flow field estimation in carotid arteries

6 citations

6 papers

cs.CL2026

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…

cs.CV2026

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…

stat.ME2026

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…

q-bio.QM20266 cited

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…

eess.IV20262 cited

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…

cs.AI2026

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 +4

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…