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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:

An insight into the current perceptions of UK radiographers on the future impact of AI on the profession: A cross-sectional survey
Clare Rainey, Tracy O’Regan, Jacqueline Matthew, et al.
Journal of medical imaging and radiation sciences (2022) Vol. 53, Iss. 3, pp. 347-361
Open Access | Times Cited: 17

Showing 17 citing articles:

Artificial Intelligence for Radiotherapy Auto-Contouring: Current Use, Perceptions of and Barriers to Implementation
Sumeet Hindocha, Kieran Zucker, R. Jena, et al.
Clinical Oncology (2023) Vol. 35, Iss. 4, pp. 219-226
Open Access | Times Cited: 36
AI implementation in the UK landscape: Knowledge of AI governance, perceived challenges and opportunities, and ways forward for radiographers
Nikolaos Stogiannos, Tracy O’Regan, Erica Scurr, et al.
Radiography (2024) Vol. 30, Iss. 2, pp. 612-621
Open Access | Times Cited: 11
A Nordic survey on artificial intelligence in the radiography profession – Is the profession ready for a culture change?
Malene Roland Vils Pedersen, Martin Weber Kusk, S. Lysdahlgaard, et al.
Radiography (2024) Vol. 30, Iss. 4, pp. 1106-1115
Open Access | Times Cited: 5
The American Society of Radiologic Technologists (ASRT) AI educator survey: A cross-sectional study to explore knowledge, experience, and use of AI within education
Nikolaos Stogiannos, Michael Jennings, Craig St George, et al.
Journal of medical imaging and radiation sciences (2024) Vol. 55, Iss. 4, pp. 101449-101449
Open Access | Times Cited: 5
Artificial Intelligence user interface preferences in radiology: A scoping review
Avneet Gill, Clare Rainey, Laura L. McLaughlin, et al.
Journal of medical imaging and radiation sciences (2025) Vol. 56, Iss. 3, pp. 101866-101866
Open Access
Nordic radiographers’ and students’ perspectives on artificial intelligence – A cross-sectional online survey
Malene Roland Vils Pedersen, Martin Weber Kusk, S. Lysdahlgaard, et al.
Radiography (2024) Vol. 30, Iss. 3, pp. 776-783
Open Access | Times Cited: 3
Efficiency, accuracy, and health professional's perspectives regarding artificial intelligence in radiology practice: A scoping review
Chanchan He, Weiqi Liu, Jing Xu, et al.
iRadiology (2024) Vol. 2, Iss. 2, pp. 156-172
Open Access | Times Cited: 3
An experimental machine learning study investigating the decision-making process of students and qualified radiographers when interpreting radiographic images
Clare Rainey, Angelina Thomas Villikudathil, Jonathan McConnell, et al.
PLOS Digital Health (2023) Vol. 2, Iss. 10, pp. e0000229-e0000229
Open Access | Times Cited: 8
An assessment of PET and CMR radiomic features for the detection of cardiac sarcoidosis
Nouf A. Mushari, Georgios Soultanidis, Lisa Duff, et al.
Frontiers in Nuclear Medicine (2024) Vol. 4
Open Access | Times Cited: 1
Allied health professionals’ perceptions of artificial intelligence in the clinical setting: a cross sectional survey (Preprint)
Jane Hoffman, Laetitia Hattingh, Lucy Shinners, et al.
JMIR Formative Research (2024) Vol. 8, pp. e57204-e57204
Open Access | Times Cited: 1
Current Radiology workforce perspective on the integration of artificial intelligence in clinical practice: A systematic review
Samuel Arkoh, Theophilus N. Akudjedu, C. Amedu, et al.
Journal of medical imaging and radiation sciences (2024) Vol. 56, Iss. 1, pp. 101769-101769
Closed Access | Times Cited: 1
Lessons on AI implementation from senior clinical practitioners: An exploratory qualitative study in medical imaging and radiotherapy in the UK
Nikolaos Stogiannos, Tracy O’Regan, Erica Scurr, et al.
Journal of medical imaging and radiation sciences (2024) Vol. 56, Iss. 1, pp. 101797-101797
Open Access | Times Cited: 1
Exploring the Utility of Cardiovascular Magnetic Resonance Radiomic Feature Extraction for Evaluation of Cardiac Sarcoidosis
Nouf A. Mushari, Georgios Soultanidis, Lisa Duff, et al.
Diagnostics (2023) Vol. 13, Iss. 11, pp. 1865-1865
Open Access | Times Cited: 3
Exploring the Potential of Artificial Intelligence in Primary Care: Insights From Stakeholders’ Perspectives
Teresa Sides, Dhouha Kbaier Ben Ismail, T. Frey, et al.
(2023)
Open Access | Times Cited: 2
Radiology staff perspectives are a key determinant for successful AI adoption in clinical practice
Michail E. Klontzas, Susan C. Shelmerdine
European Journal of Radiology (2024) Vol. 180, pp. 111692-111692
Closed Access
The knowledge and perception of patients in Malta towards artificial intelligence in medical imaging
Francesca Xuereb, Dr Jonathan L Portelli
Journal of medical imaging and radiation sciences (2024) Vol. 55, Iss. 4, pp. 101743-101743
Open Access
Allied Health Professionals’ Perceptions of Artificial Intelligence in the Clinical Setting: Cross-Sectional Survey (Preprint)
Jane Hoffman, Laetitia Hattingh, Lucy Shinners, et al.
(2024)
Closed Access
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