Stephen Gilbert

2.8k total citations
101 papers, 1.5k citations indexed

About

Stephen Gilbert is a scholar working on Health Informatics, Cardiology and Cardiovascular Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Stephen Gilbert has authored 101 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Health Informatics, 20 papers in Cardiology and Cardiovascular Medicine and 20 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Stephen Gilbert's work include Artificial Intelligence in Healthcare and Education (26 papers), Mobile Health and mHealth Applications (11 papers) and Digital Mental Health Interventions (9 papers). Stephen Gilbert is often cited by papers focused on Artificial Intelligence in Healthcare and Education (26 papers), Mobile Health and mHealth Applications (11 papers) and Digital Mental Health Interventions (9 papers). Stephen Gilbert collaborates with scholars based in Germany, United Kingdom and France. Stephen Gilbert's co-authors include Paul Wicks, Arun V. Holden, Alan P. Benson, Jakob Nikolas Kather, Tom Melvin, Hugh Harvey, Olivier Bernus, F S Fay, Katie J. Perry and Isabella C. Wiest and has published in prestigious journals such as Nature Medicine, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Stephen Gilbert

94 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephen Gilbert Germany 23 369 355 344 225 198 101 1.5k
Marcus A. Badgeley United States 16 138 0.4× 431 1.2× 708 2.1× 613 2.7× 225 1.1× 21 2.0k
Alexander W. Charney United States 21 177 0.5× 291 0.8× 167 0.5× 225 1.0× 243 1.2× 68 2.0k
Emma Chen United States 7 91 0.2× 593 1.7× 414 1.2× 456 2.0× 88 0.4× 13 1.4k
Kyle Lam United Kingdom 13 107 0.3× 473 1.3× 245 0.7× 276 1.2× 39 0.2× 32 1.2k
Julián Acosta United States 14 126 0.3× 231 0.7× 245 0.7× 234 1.0× 116 0.6× 45 1.2k
Danton Char United States 13 125 0.3× 771 2.2× 368 1.1× 382 1.7× 44 0.2× 45 1.6k
Oishi Banerjee United States 5 102 0.3× 912 2.6× 687 2.0× 773 3.4× 150 0.8× 7 2.2k
Garry Choy United States 25 104 0.3× 345 1.0× 1.4k 4.0× 238 1.1× 191 1.0× 50 2.5k
Corey Arnold United States 24 80 0.2× 104 0.3× 430 1.3× 657 2.9× 162 0.8× 105 1.7k
Seth J. Berkowitz United States 14 81 0.2× 391 1.1× 705 2.0× 626 2.8× 111 0.6× 29 1.4k

Countries citing papers authored by Stephen Gilbert

Since Specialization
Citations

This map shows the geographic impact of Stephen Gilbert'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 Stephen Gilbert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen Gilbert more than expected).

Fields of papers citing papers by Stephen Gilbert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen Gilbert. 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 Stephen Gilbert. The network helps show where Stephen Gilbert may publish in the future.

Co-authorship network of co-authors of Stephen Gilbert

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen Gilbert. A scholar is included among the top collaborators of Stephen Gilbert 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 Stephen Gilbert. Stephen Gilbert is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Inojosa, Hernán, et al.. (2025). Education Research: Can Large Language Models Match MS Specialist Training?. PubMed. 4(4). e200260–e200260.
5.
Klein, Jan, et al.. (2025). The effects of information and communication technology (ICT) implementation on psychophysiological markers of stress: a systematic review. Behaviour and Information Technology. 44(20). 5002–5027. 1 indexed citations
6.
Gilbert, Stephen, et al.. (2025). A roadmap for safe, regulation-compliant Living Labs for AI and digital health development. Science Advances. 11(20). eadv7719–eadv7719. 3 indexed citations
7.
Li, Ben & Stephen Gilbert. (2024). Artificial Intelligence awarded two Nobel Prizes for innovations that will shape the future of medicine. npj Digital Medicine. 7(1). 336–336. 16 indexed citations
8.
Gilbert, Stephen, et al.. (2024). How might Hospital at Home enable a greener and healthier future?. npj Digital Medicine. 7(1). 252–252. 2 indexed citations
9.
Riedemann, Lars, et al.. (2024). The path forward for large language models in medicine is open. npj Digital Medicine. 7(1). 339–339. 13 indexed citations
10.
Inojosa, Hernán, Isabel Voigt, Dyke Ferber, et al.. (2024). Integrating large language models in care, research, and education in multiple sclerosis management. Multiple Sclerosis Journal. 30(11-12). 1392–1401. 7 indexed citations
11.
Gilbert, Stephen, et al.. (2024). Consideration of Cybersecurity Risks in the Benefit-Risk Analysis of Medical Devices: Scoping Review. Journal of Medical Internet Research. 26. e65528–e65528. 4 indexed citations
12.
Wiest, Isabella C., Stephen Gilbert, & Jakob Nikolas Kather. (2024). From research to reality: The role of artificial intelligence applications in HCC care. Clinical Liver Disease. 23(1). e0136–e0136. 5 indexed citations
13.
Li, Phoebe, Robin Williams, Stephen Gilbert, & Stuart Anderson. (2023). Regulating Artificial Intelligence and Machine Learning-Enabled Medical Devices in Europe and the United Kingdom. SHILAP Revista de lepidopterología. 5(2). 94–113. 12 indexed citations
14.
Fraser, Alan G., Bart Bijnens, Nico Bruining, et al.. (2023). Artificial intelligence in medical device software and high-risk medical devices – a review of definitions, expert recommendations and regulatory initiatives. Expert Review of Medical Devices. 20(6). 467–491. 27 indexed citations
15.
Kirsten, Toralf, et al.. (2023). The Social Contract for Health and Wellness Data Sharing Needs a Trusted Standardized Consent. SHILAP Revista de lepidopterología. 1(4). 527–533. 6 indexed citations
16.
Wekenborg, Magdalena, et al.. (2023). Holistic Human-Serving Digitization of Health Care Needs Integrated Automated System-Level Assessment Tools. Journal of Medical Internet Research. 25. e50158–e50158. 12 indexed citations
17.
Peven, Kimberly, Yusuf Cem Kaplan, Adam Cunningham, et al.. (2023). Assessment of a Digital Symptom Checker Tool's Accuracy in Suggesting Reproductive Health Conditions: Clinical Vignettes Study. JMIR mhealth and uhealth. 11. e46718–e46718. 4 indexed citations
18.
Mueller, Tobias, Stephen Gilbert, Jan Multmeier, et al.. (2022). Safety of Triage Self-assessment Using a Symptom Assessment App for Walk-in Patients in the Emergency Care Setting: Observational Prospective Cross-sectional Study. JMIR mhealth and uhealth. 10(3). e32340–e32340. 25 indexed citations
19.
Serfózó, Péter, et al.. (2022). A Novel Diagnostic Decision Support System for Medical Professionals: Prospective Feasibility Study. JMIR Formative Research. 6(3). e29943–e29943. 3 indexed citations
20.
Burger, Alexa, et al.. (2018). Planar cell polarity signalling coordinates heart tube remodelling through tissue-scale polarisation of actomyosin activity. Nature Communications. 9(1). 2161–2161. 33 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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