Kahn, Charles E.

Checklist for Artificial Intelligence in Medical Imaging (CLAIM): a guide for authors and reviewers

Mongan, J., Moy, L., & Kahn, C. E. (2020) · Radiology: Artificial Intelligence

Artificial Intelligence in Healthcare and EducationAcademic Writing and Publishing

Cited by 1,443

Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update

Tejani, A. S., Klontzas, M. E., Gatti, A. A., Mongan, J. T., Moy, L., Park, S. H., Kahn, C. E., Panel, F. T. C. 2. U., Abbara, S., Afat, S., et al. (2024) · Radiology: Artificial Intelligence

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

Cited by 570

Understanding metric-related pitfalls in image analysis validation

Reinke, A., Tizabi, M. D., Baumgartner, M., Eisenmann, M., Heckmann-Nötzel, D., Kavur, A. E., Rädsch, T., Sudre, C. H., Acion, L., Antonelli, M., et al. (2024) · Nature Methods

Cell Image Analysis TechniquesMedical Image Segmentation Techniques

Cited by 241

PRISMA AI reporting guidelines for systematic reviews and meta-analyses on AI in healthcare

Cacciamani, G. E., Chu, T. N., Sanford, D. I., Abreu, A., Duddalwar, V., Oberai, A., Kuo, C.-C. J., Liu, X., Denniston, A. K., Vasey, B., et al. (2023) · Nature Medicine

Meta-analysis and systematic reviewsArtificial Intelligence in Healthcare and Education

Cited by 143

Common Limitations of Image Processing Metrics: A Picture Story

Reinke, A., Tizabi, M. D., Sudre, C. H., Eisenmann, M., Rädsch, T., Baumgartner, M., Acion, L., Antonelli, M., Arbel, T., Bakas, S., et al. (2021) · arXiv

Medical Image Segmentation TechniquesCell Image Analysis Techniques

Cited by 126

From images to actions: Opportunities for artificial intelligence in radiology

Kahn, C. E. (2017) · Radiology

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

Cited by 88

Readability of radiology reports: implications for patient-centered care

Martin-Carreras, T., Cook, T. S., & Kahn, C. E. (2019) · Clinical Imaging

Radiology practices and educationHealth Literacy and Information Accessibility

Cited by 87

AI Reporting Guidelines: How to Select the Best One for Your Research

Klontzas, M. E., Gatti, A. A., Tejani, A. S., & Kahn, C. E. (2023) · Radiology: Artificial Intelligence

Artificial Intelligence in Healthcare and EducationMeta-analysis and systematic reviews

Cited by 66

Consensus statements on the current landscape of artificial intelligence applications in endoscopy, addressing roadblocks, and advancing artificial intelligence in gastroenterology

Parasa, S., Berzin, T., Leggett, C., Gross, S., Repici, A., Ahmad, O. F., Chiang, A., Coelho-Prabhu, N., Cohen, J., Dekker, E., et al. (2025) · Gastrointestinal Endoscopy

Artificial Intelligence in Healthcare and EducationAI in cancer detection

Cited by 64

Metrics reloaded: Recommendations for image analysis validation

Maier-Hein, L., Reinke, A., Godau, P., Tizabi, M. D., Buettner, F., Christodoulou, E., Glocker, B., Isensee, F., Kleesiek, J., Kozubek, M., et al. (2022) · arXiv

Cell Image Analysis TechniquesMedical Image Segmentation Techniques

Cited by 59

DICOMweb™: Background and Application of the Web Standard for Medical Imaging

Genereaux, B. W., Dennison, D. K., Ho, K., Horn, R., Silver, E. L., O’Donnell, K., & Kahn, C. E. (2018) · Journal of Digital Imaging

Electronic Health Records SystemsArtificial Intelligence in Healthcare and Education

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