Calls for papers, journal updates, and policy news from Eldenhall.
We invite original research on the safe validation and deployment of generative AI and LLMs across diagnosis, decision support, and clinical documentation.
Read the latest peer-reviewed research on foundation models, medical imaging, federated learning, and clinical risk prediction.
New author guidance on external validation, calibration, fairness, and transparent reporting for computational diagnostic studies.
A themed collection on foundation and vision-language models for radiology, pathology, and diagnostic imaging. Submissions welcome.
We welcome leading researchers strengthening our editorial expertise across natural language processing and imaging AI.
Call for papers on LLMs for clinical notes, summarisation, coding, and workflow, with an emphasis on safety and evaluation.
Our editors highlight a prospective multicentre study on explainable deep learning in radiology workflow.
Authors are now asked to share code and de-identified data where possible to support reproducibility of computational studies.
Recognising the essential work of our reviewers, review activity can be deposited to ORCID.
Updated policy for authors and reviewers on disclosing the use of generative AI tools in manuscript preparation.
We are expanding our reviewer pool. Researchers with expertise in AI for healthcare are invited to join.
Our multidisciplinary journal for AI and data-driven research in healthcare and medicine launches and begins accepting manuscripts.
A new open-access journal at the intersection of artificial intelligence, data science, and clinical medicine is announced.