Staking our CLAIM
by Charles E. Kahn, Jr, MD, MS, Editor, Radiology: Artificial Intelligence
Readers of scientific articles may be familiar with reporting standards that help authors include the information needed to evaluate their research.
In this month’s issue of the journal, we introduce a guideline for Artificial Intelligence papers in medical imaging. It’s called CLAIM: the Checklist for AI in Medical Imaging.
The CLAIM guideline is the result of a multidisciplinary group effort, involving scientific expertise in machine learning, data science, imaging science, and radiology—along with experienced journal editors. I’m truly fortunate to have been joined in this effort by Dr. John Mongan and Dr. Linda Moy. John is Associate Editor of this journal and serves as Vice Chair of RSNA’s Machine Learning Steering Committee. Linda is Senior Deputy Editor for Radiology. Both are active radiology AI researchers with in-depth experience as scientific reviewers and editors.
Along with imaging AI applications, CLAIM goes beyond diagnosis and classification. CLAIM can be applied to triage, image generation, image reconstruction, and natural language processing (NLP) of imaging reports.
CLAIM is not specific to radiology. It will be of value to other medical specialties that use imaging – including pathology, dermatology, ophthalmology, and endoscopy.
The Radiology: Artificial Intelligence Editorial Board has adopted CLAIM for manuscripts submitted to this journal. We believe that CLAIM will help authors and reviewers assure that work submitted to the journal can be evaluated rigorously and will promote the highest quality of AI research.
We’ve staked our CLAIM, and we encourage your feedback.
The latest CLAIM updates and resources can be found on our main CLAIM informational page
Charles E. Kahn, Jr, MD, MS is professor and vice chair of radiology at the University of Pennsylvania, and editor of Radiology: Artificial Intelligence.
Follow him on Twitter: @cekahn, @Radiology_AI