3 papers
cs.CL2026
Tracking Cancer Through Text: Longitudinal Extraction From Radiology Reports Using Open-Source Large Language Models
Luc Builtjes, Alessa Hering
Radiology reports capture crucial longitudinal information on tumor burden, treatment response, and disease progression, yet their unstructured narrative format complicates automat…
cs.CV2026
Designing UNICORN: a Unified Benchmark for Imaging in Computational Pathology, Radiology, and Natural Language
Michelle Stegeman, Lena Philipp, Fennie van der Graaf +19
Medical foundation models show promise to learn broadly generalizable features from large, diverse datasets. This could be the base for reliable cross-modality generalization and r…
cs.CL2025
Leveraging Open-Source Large Language Models for Clinical Information Extraction in Resource-Constrained Settings
Luc Builtjes, Joeran Bosma, Mathias Prokop +2
Medical reports contain rich clinical information but are often unstructured and written in domain-specific language, posing challenges for information extraction. While proprietar…