Radiology AI makes consistent diagnoses using 3D images from different health centres

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Abstract

To meet the growing demand for radiology artificial-intelligence tools, a 3D vision–language model called Merlin was trained on abdominal computed-tomography scans, radiology reports and electronic health records. Merlin demonstrated stronger off-the-shelf performance than did other vision–language models across three hospital sites distinct from the initial training centre, highlighting its potential for broader clinical adoption. Vision–language model outperforms second-best models by an average of 20% across hospital sites.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Multimodal Machine Learning Applications Radiomics and Machine Learning in Medical Imaging

Publication details

Journal / source
Nature
Publication date
4 March 2026
Language
EN