activity
20242026
most citedAI in radiological imaging of soft-tissue and bone tumours: a systematic review evaluating against CLAIM and FUTURE-AI guidelines

20 citations · 31 across the 4 of their papers we have counts for

collaborators

4 papers

eess.IV2026

Cross-Attention Multimodal Learning for Predicting Response to Neoadjuvant Imatinib in Gastrointestinal Stromal Tumors: A Multicenter Retrospective Study

Fariba Tohidinezhad, Douwe J. Spaanderman, Natalia Oviedo Acosta +14

Background: Response to neoadjuvant imatinib in gastrointestinal stromal tumors (GISTs) is highly variable and cannot be reliably predicted using current clinical or molecular mark…

cs.CL2025★ 2 cited

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,…

cs.AI2024★ 20 cited

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…

eess.IV2024★ 9 cited

Minimally Interactive Segmentation of Soft-Tissue Tumors on CT and MRI using Deep Learning

Douwe J. Spaanderman, Martijn P. A. Starmans, Gonnie C. M. van Erp +9

Segmentations are crucial in medical imaging to obtain morphological, volumetric, and radiomics biomarkers. Manual segmentation is accurate but not feasible in the radiologist's cl…