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Updating the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) for reporting AI research

Nature Machine Intelligence volume 5, pages 950–951 (2023)Cite this article

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The Checklist for Artificial Intelligence in Medical Imaging (CLAIM) promotes transparent and reproducible reporting of artificial intelligence (AI) research in medical imaging, and has been cited more than 420 times1. CLAIM’s seven categories — addressing a manuscript’s title, abstract, introduction, methods, results, discussion, and other information — comprise 42 checklist items. The CLAIM guideline serves as a ‘best practice’ recommendation for reporting original research in AI-supported medical imaging; it provides researchers a baseline to document their work and offers reviewers a framework for organized assessment.

Applications of AI in medical imaging have continued to grow since the publication of CLAIM in 2020. That growth creates a demand on peer-reviewed medical journals to standardize required reporting elements that reflect this dynamic field. Incomplete or inconsistent reporting can impede the development and clinical translation of proposed AI techniques or applications2. CLAIM seeks to assure complete and consistent reporting of medical imaging AI science. Final peer-reviewed manuscripts have demonstrated greater adherence to CLAIM than those on preprint platforms2. To address the field’s rapid evolution, we seek to update the CLAIM guideline.

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Authors and Affiliations

  1. Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Ali S. Tejani

  2. Department of Radiology, University of Crete School of Medicine, Heraklion, Crete, Greece

    Michail E. Klontzas

  3. Department of Medical Imaging, University Hospital of Heraklion, Crete, Greece

    Michail E. Klontzas

  4. Department of Radiology, Stanford University, Stanford, CA, USA

    Anthony A. Gatti

  5. Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA

    John Mongan

  6. Department of Radiology, New York University Grossman School of Medicine, New York City, NY, USA

    Linda Moy

  7. Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea

    Seong Ho Park

  8. Department of Radiology and Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, USA

    Charles E. Kahn Jr

Authors
  1. Ali S. Tejani
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  2. Michail E. Klontzas
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  3. Anthony A. Gatti
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  4. John Mongan
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  5. Linda Moy
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  6. Seong Ho Park
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  7. Charles E. Kahn Jr
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Corresponding author

Correspondence to Charles E. Kahn Jr.

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Competing interests

C.E.K. reports salary and travel support from Radiological Society of North America (RSNA) for services as editor of Radiology: Artificial Intelligence; and travel expenses from the Sectra USA Radiology Advisory Panel. M.E.K. reports meeting attendance support from Bayer. A.A.G. is a shareholder of NeuralSeg Ltd. L.M. reports salary and travel support from Radiological Society of North America (RSNA) for services as Editor of Radiology; research grants from Siemens, Gordon and Betty Moore Foundation, Mary Kay Foundation and Google; personal fees from Lunit, Inc.; personal fees from and served on the advisory board of ICAD; personal fees from Guerbet Inc; and meeting and travel expenses from the British Society of Breast Radiology, European Society of Breast Imaging. J.T.M. reports grant funding from Siemens; royalties from GE; unpaid consulting from Nuance/Microsoft; and spouse employment at Annexon Biosciences. S.H.P. has received consultant honoraria from Bayer and Korean Society of Radiology; and meeting and travel expenses from Korean Society of Radiology.

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Tejani, A.S., Klontzas, M.E., Gatti, A.A. et al. Updating the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) for reporting AI research. Nat Mach Intell 5, 950–951 (2023). https://doi.org/10.1038/s42256-023-00717-2

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