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Updated: Sep 18, 2025

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
Published on: July 11, 2025
Interventional Radiology Reporting Standards and Checklist for Artificial Intelligence Research Evaluation (iCARE)
James T Anibal1,2, Hannah B Huth3, Tom Boeken4
1Center for Interventional Oncology, NIH Clinical Center, National Cancer Institute, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health (NIH), Bethesda, MD, 20892, USA. anibal.james@nih.gov.
Abstract:
As artificial intelligence (AI) becomes increasingly prevalent within interventional radiology (IR) research and clinical practice, steps must be taken to ensure the robustness of novel technological systems presented in peer-reviewed journals. This report introduces comprehensive standards and an evaluation checklist (iCARE) that covers the application of modern AI methods in IR-specific contexts. The iCARE checklist encompasses the full "code-to-clinic" pipeline of AI development, including dataset curation, pre-training, task-specific training, explainability, privacy protection, bias mitigation, reproducibility, and model deployment. The iCARE checklist aims to support the development of safe, generalizable technologies for enhancing IR workflows, the delivery of care, and patient outcomes.
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