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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

To buy or not to buy—evaluating commercial AI solutions in radiology (the ECLAIR guidelines)
Patrick Omoumi, Alexis Ducarouge, Antoine Tournier, et al.
European Radiology (2021) Vol. 31, Iss. 6, pp. 3786-3796
Open Access | Times Cited: 130

Showing 1-25 of 130 citing articles:

Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction
David Nam, Julius Chapiro, Valérie Paradis, et al.
JHEP Reports (2022) Vol. 4, Iss. 4, pp. 100443-100443
Open Access | Times Cited: 140
Evaluation framework to guide implementation of AI systems into healthcare settings
Sandeep Reddy, Wendy Rogers, Ville‐Petteri Mäkinen, et al.
BMJ Health & Care Informatics (2021) Vol. 28, Iss. 1, pp. e100444-e100444
Open Access | Times Cited: 108
Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology
Roxana Daneshjou, Catarina Barata, Brigid Betz‐Stablein, et al.
JAMA Dermatology (2021) Vol. 158, Iss. 1, pp. 90-90
Open Access | Times Cited: 106
Developing, implementing and governing artificial intelligence in medicine: a step-by-step approach to prevent an artificial intelligence winter
Davy van de Sande, Michel E. van Genderen, Jim M. Smit, et al.
BMJ Health & Care Informatics (2022) Vol. 29, Iss. 1, pp. e100495-e100495
Open Access | Times Cited: 92
Methods for Clinical Evaluation of Artificial Intelligence Algorithms for Medical Diagnosis
Seong Ho Park, Kyunghwa Han, Hye Young Jang, et al.
Radiology (2022) Vol. 306, Iss. 1, pp. 20-31
Closed Access | Times Cited: 73
Environmental Sustainability and AI in Radiology: A Double-Edged Sword
Florence X. Doo, Jan Vosshenrich, Tessa S. Cook, et al.
Radiology (2024) Vol. 310, Iss. 2
Closed Access | Times Cited: 52
Developing, purchasing, implementing and monitoring AI tools in radiology: practical considerations. A multi-society statement from the ACR, CAR, ESR, RANZCR & RSNA
Adrian P. Brady, Bibb Allen, Jaron Chong, et al.
Insights into Imaging (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 34
Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement from the ACR, CAR, ESR, RANZCR and RSNA
Adrian P. Brady, Bibb Allen, Jaron Chong, et al.
Radiology Artificial Intelligence (2024) Vol. 6, Iss. 1
Open Access | Times Cited: 24
How AI May Transform Musculoskeletal Imaging
Ali Guermazi, Patrick Omoumi, Mickaël Tordjman, et al.
Radiology (2024) Vol. 310, Iss. 1
Closed Access | Times Cited: 17
External validation of a commercially available deep learning algorithm for fracture detection in children
M. Dupuis, Léo Delbos, Raphaël Veil, et al.
Diagnostic and Interventional Imaging (2021) Vol. 103, Iss. 3, pp. 151-159
Open Access | Times Cited: 64
Nuclear Medicine and Artificial Intelligence: Best Practices for Evaluation (the RELAINCE Guidelines)
Abhinav K. Jha, Tyler Bradshaw, Irène Buvat, et al.
Journal of Nuclear Medicine (2022) Vol. 63, Iss. 9, pp. 1288-1299
Open Access | Times Cited: 61
Technical and clinical validation of commercial automated volumetric MRI tools for dementia diagnosis—a systematic review
Hugh Pemberton, Lara A. M. Zaki, Olivia Goodkin, et al.
Neuroradiology (2021) Vol. 63, Iss. 11, pp. 1773-1789
Open Access | Times Cited: 59
Evaluation and Real-World Performance Monitoring of Artificial Intelligence Models in Clinical Practice: Try It, Buy It, Check It
Bibb Allen, Keith J. Dreyer, Robert Stibolt, et al.
Journal of the American College of Radiology (2021) Vol. 18, Iss. 11, pp. 1489-1496
Closed Access | Times Cited: 57
Oncologic Imaging and Radiomics: A Walkthrough Review of Methodological Challenges
Arnaldo Stanzione, Renato Cuocolo, Lorenzo Ugga, et al.
Cancers (2022) Vol. 14, Iss. 19, pp. 4871-4871
Open Access | Times Cited: 44
Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement From the ACR, CAR, ESR, RANZCR & RSNA
Adrian P. Brady, Bibb Allen, Jaron Chong, et al.
Canadian Association of Radiologists Journal (2024) Vol. 75, Iss. 2, pp. 226-244
Open Access | Times Cited: 14
A holistic approach to implementing artificial intelligence in radiology
Bomi Kim, Stephan R. Romeijn, Mark A. van Buchem, et al.
Insights into Imaging (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 14
Comparison of Commercial AI Software Performance for Radiograph Lung Nodule Detection and Bone Age Prediction
Kicky G. van Leeuwen, Steven Schalekamp, Matthieu Rutten, et al.
Radiology (2024) Vol. 310, Iss. 1
Closed Access | Times Cited: 13
Empirical data drift detection experiments on real-world medical imaging data
Ali Kore, Elyar Abbasi Bavil, Vallijah Subasri, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 11
Developing, purchasing, implementing and monitoring AI tools in radiology: Practical considerations. A multi‐society statement from the ACR, CAR, ESR, RANZCR & RSNA
Adrian P. Brady, Bibb Allen, Jaron Chong, et al.
Journal of Medical Imaging and Radiation Oncology (2024) Vol. 68, Iss. 1, pp. 7-26
Open Access | Times Cited: 10
Radiology AI Deployment and Assessment Rubric (RADAR) to bring value-based AI into radiological practice
Bart-Jan Boverhof, Ken Redekop, Daniël Bos, et al.
Insights into Imaging (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 10
Women’s perceptions and attitudes towards the use of AI in mammography in Sweden: a qualitative interview study
Jennifer Viberg Johansson, Karin Dembrower, Fredrik Strand, et al.
BMJ Open (2024) Vol. 14, Iss. 2, pp. e084014-e084014
Open Access | Times Cited: 10
New Frontiers in Breast Cancer Imaging: The Rise of AI
Stephanie Shamir, Arielle Sasson, Laurie R. Margolies, et al.
Bioengineering (2024) Vol. 11, Iss. 5, pp. 451-451
Open Access | Times Cited: 10
AI Applications for Thoracic Imaging: Considerations for Best Practice
Eui Jin Hwang, Jin Mo Goo, Chang Min Park
Radiology (2025) Vol. 314, Iss. 2
Closed Access | Times Cited: 1
DeepLesionBrain: Towards a broader deep-learning generalization for multiple sclerosis lesion segmentation
Reda Abdellah Kamraoui, Vinh‐Thong Ta, Thomas Tourdias, et al.
Medical Image Analysis (2021) Vol. 76, pp. 102312-102312
Open Access | Times Cited: 52
Will the EU Medical Device Regulation help to improve the safety and performance of medical AI devices?
Emilia Niemiec
Digital Health (2022) Vol. 8, pp. 205520762210890-205520762210890
Open Access | Times Cited: 38
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