5 papers
Do Medical Foundation Models Generalize on the African Brain?
Kaouther Mouheb, Gonzalo Esteban Mosquera Rojas, Juancito van Leeuwen +2
Medical foundation models (FMs) are increasingly used for brain MRI analysis. However, their evaluation remains dominated by high-resource datasets, leaving generalization to Afric…
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…
TriALS: Triphasic-Aided Liver Lesion Segmentation Benchmark in Non-Contrast CT
Marawan Elbatel, Mohamed Ghonim, Jiaji Mao +62
Automated segmentation of liver lesions on non-contrast computed tomography (NCCT) is clinically important but fundamentally challenging, particularly in low-resource settings acro…
Evaluating Open-Weight Large Language Models for Structured Data Extraction from Narrative Medical Reports Across Multiple Use Cases and Languages
Douwe J. Spaanderman, Karthik Prathaban, Petr Zelina +20
Large language models (LLMs) are increasingly used to extract structured information from free-text clinical records, but prior work often focuses on single tasks, limited models,…
An automated machine learning framework to optimize radiomics model construction validated on twelve clinical applications
Martijn P. A. Starmans, Sebastian R. van der Voort, Thomas Phil +43
Predicting clinical outcomes from medical images using quantitative features (``radiomics'') requires many method design choices, Currently, in new clinical applications, finding t…