Lauren Oakden‐Rayner

4.0k total citations
19 papers, 380 citations indexed

About

Lauren Oakden‐Rayner is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Lauren Oakden‐Rayner has authored 19 papers receiving a total of 380 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Health Informatics, 10 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Biomedical Engineering. Recurrent topics in Lauren Oakden‐Rayner's work include Artificial Intelligence in Healthcare and Education (10 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Radiology practices and education (5 papers). Lauren Oakden‐Rayner is often cited by papers focused on Artificial Intelligence in Healthcare and Education (10 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Radiology practices and education (5 papers). Lauren Oakden‐Rayner collaborates with scholars based in Australia, United States and Canada. Lauren Oakden‐Rayner's co-authors include Melissa D. McCradden, Marzyeh Ghassemi, Ben Glocker, Xiaoxuan Liu, Alastair K. Denniston, Lyle J. Palmer, Christoph Wald, Daniel Pinto dos Santos, Minyan Zeng and Bibb Allen and has published in prestigious journals such as Arthritis Research & Therapy, Seminars in Arthritis and Rheumatism and Frontiers in Neurology.

In The Last Decade

Lauren Oakden‐Rayner

16 papers receiving 377 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lauren Oakden‐Rayner Australia 11 207 152 99 64 48 19 380
Taiki Nozaki Japan 10 235 1.1× 242 1.6× 130 1.3× 65 1.0× 52 1.1× 19 490
K. Elizabeth Hawk United States 10 139 0.7× 329 2.2× 107 1.1× 101 1.6× 58 1.2× 18 569
Balthasar Schachtner Germany 9 275 1.3× 255 1.7× 195 2.0× 35 0.5× 62 1.3× 22 502
Alexander Merritt United States 5 248 1.2× 155 1.0× 93 0.9× 89 1.4× 14 0.3× 7 436
Ashik Amlani United Kingdom 5 257 1.2× 161 1.1× 75 0.8× 39 0.6× 37 0.8× 7 366
Keerthini Muthuswamy United Kingdom 7 257 1.2× 167 1.1× 75 0.8× 35 0.5× 21 0.4× 13 422
Shannon L. Walston Japan 15 316 1.5× 326 2.1× 138 1.4× 57 0.9× 67 1.4× 30 567
Christian Bluethgen Switzerland 9 283 1.4× 207 1.4× 265 2.7× 46 0.7× 34 0.7× 11 566
Keith Dreyer United States 4 158 0.8× 169 1.1× 75 0.8× 61 1.0× 17 0.4× 6 275
Irfan Ahmed United Kingdom 6 112 0.5× 76 0.5× 86 0.9× 22 0.3× 32 0.7× 16 366

Countries citing papers authored by Lauren Oakden‐Rayner

Since Specialization
Citations

This map shows the geographic impact of Lauren Oakden‐Rayner's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lauren Oakden‐Rayner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lauren Oakden‐Rayner more than expected).

Fields of papers citing papers by Lauren Oakden‐Rayner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lauren Oakden‐Rayner. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lauren Oakden‐Rayner. The network helps show where Lauren Oakden‐Rayner may publish in the future.

Co-authorship network of co-authors of Lauren Oakden‐Rayner

This figure shows the co-authorship network connecting the top 25 collaborators of Lauren Oakden‐Rayner. A scholar is included among the top collaborators of Lauren Oakden‐Rayner based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lauren Oakden‐Rayner. Lauren Oakden‐Rayner is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Oakden‐Rayner, Lauren, Ranjeny Thomas, Deepti Gupta, et al.. (2025). AI automated radiographic scoring in rheumatoid arthritis: Shedding light on barriers to implementation through comprehensive evaluation. Seminars in Arthritis and Rheumatism. 74. 152761–152761.
2.
McCradden, Melissa D., Mjaye Mazwi, & Lauren Oakden‐Rayner. (2025). Can an accurate model be bad?. Patterns. 6(4). 101205–101205.
3.
Brady, Adrian P., Bibb Allen, Jaron Chong, et al.. (2024). Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement from the ACR, CAR, ESR, RANZCR and RSNA. Radiology Artificial Intelligence. 6(1). e230513–e230513. 26 indexed citations
4.
Semmler, Carolyn, et al.. (2024). Medical artificial intelligence for clinicians: the lost cognitive perspective. The Lancet Digital Health. 6(8). e589–e594. 16 indexed citations
5.
Oakden‐Rayner, Lauren, et al.. (2024). Prognostic modeling in early rheumatoid arthritis: reconsidering the predictive role of disease activity scores. Clinical Rheumatology. 43(5). 1503–1512.
6.
Brady, Adrian P., Bibb Allen, Jaron Chong, et al.. (2024). Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement From the ACR, CAR, ESR, RANZCR & RSNA. Journal of the American College of Radiology. 21(8). 1292–1310. 11 indexed citations
7.
Brady, Adrian P., Bibb Allen, Jaron Chong, et al.. (2024). Developing, purchasing, implementing and monitoring AI tools in radiology: practical considerations. A multi-society statement from the ACR, CAR, ESR, RANZCR & RSNA. Insights into Imaging. 15(1). 16–16. 36 indexed citations
8.
Brady, Adrian P., Bibb Allen, Jaron Chong, et al.. (2024). Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement From the ACR, CAR, ESR, RANZCR & RSNA. Canadian Association of Radiologists Journal. 75(2). 226–244. 21 indexed citations
9.
Oakden‐Rayner, Lauren, et al.. (2024). Impact of Transfer Learning Using Local Data on Performance of a Deep Learning Model for Screening Mammography. Radiology Artificial Intelligence. 6(4). e230383–e230383. 1 indexed citations
10.
Bondi, Elizabeth, Thomas Hartvigsen, Swami Sankaranarayanan, et al.. (2023). Taking Off with AI: Lessons from Aviation for Healthcare. 1–14. 3 indexed citations
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13.
Liu, Xiaoxuan, Ben Glocker, Melissa D. McCradden, et al.. (2022). The medical algorithmic audit. The Lancet Digital Health. 4(5). e384–e397. 121 indexed citations
14.
Oakden‐Rayner, Lauren, Christopher McMaster, Minyan Zeng, et al.. (2022). Artificial intelligence and the future of radiographic scoring in rheumatoid arthritis: a viewpoint. Arthritis Research & Therapy. 24(1). 268–268. 15 indexed citations
15.
Franke, Kyle B., David Wang, Yiran Tan, et al.. (2022). Professionalism and clinical short answer question marking with machine learning. Internal Medicine Journal. 52(7). 1268–1271. 6 indexed citations
16.
Oakden‐Rayner, Lauren, William A. Gale, Matthew P. Lungren, et al.. (2022). Validation and algorithmic audit of a deep learning system for the detection of proximal femoral fractures in patients in the emergency department: a diagnostic accuracy study. The Lancet Digital Health. 4(5). e351–e358. 55 indexed citations
17.
Zeng, Minyan, Lauren Oakden‐Rayner, L.T. Smith, et al.. (2022). Pre-thrombectomy prognostic prediction of large-vessel ischemic stroke using machine learning: A systematic review and meta-analysis. Frontiers in Neurology. 13. 945813–945813. 10 indexed citations
18.
Newsome, Janice, et al.. (2022). Fostering an inclusive workplace for LGBTQIA+ people in radiology and radiation oncology. Journal of Medical Imaging and Radiation Oncology. 67(2). 193–199. 1 indexed citations
19.
Oakden‐Rayner, Lauren, et al.. (2022). Assessment of a single‐pass venous phase CT chest, abdomen and pelvis and dual‐energy CT in general oncology outpatients. Journal of Medical Imaging and Radiation Oncology. 67(4). 349–356. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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