Volumetric computed tomography (CT) segmentation supports quantitative image analysis, but most AI-based methods remain organ-specific, with fragmented models, inconsistent label definitions, and heterogeneous training and evaluation protocols. Here we present CADS, a unified data–model framework for scalable and gen...
Murong Xu, Fernando Navarro, Maksym Fritsak et al.· Nature Communications· 0 citations
Background The rapid growth of biomedical publishing in radiation oncology has created a need for automated methods to extract structured information from unstructured text. Large language models (LLMs) show promise in biomedical natural language processing, but their use for clinical trial data curation remains to be...
F. Dennstaedt, Lena Kretzschmar, N. Cihoric et al.· Oncology· 0 citations
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