Robbert Struyven

1.4k total citations
19 papers, 248 citations indexed

About

Robbert Struyven is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Health Informatics. According to data from OpenAlex, Robbert Struyven has authored 19 papers receiving a total of 248 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Radiology, Nuclear Medicine and Imaging, 13 papers in Ophthalmology and 2 papers in Health Informatics. Recurrent topics in Robbert Struyven's work include Retinal Imaging and Analysis (14 papers), Retinal and Optic Conditions (11 papers) and Retinal Diseases and Treatments (10 papers). Robbert Struyven is often cited by papers focused on Retinal Imaging and Analysis (14 papers), Retinal and Optic Conditions (11 papers) and Retinal Diseases and Treatments (10 papers). Robbert Struyven collaborates with scholars based in United Kingdom, United States and Netherlands. Robbert Struyven's co-authors include Pearse A. Keane, Siegfried K. Wagner, Konstantinos Balaskas, Nikolas Pontikos, Dun Jack Fu, Bart Liefers, Gongyu Zhang, Daniel C. Alexander, Mark A. Chia and Livia Faes and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and American Journal of Ophthalmology.

In The Last Decade

Robbert Struyven

17 papers receiving 245 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Robbert Struyven United Kingdom 8 179 157 23 19 17 19 248
Mark A. Chia United Kingdom 8 161 0.9× 144 0.9× 25 1.1× 20 1.1× 16 0.9× 20 266
Shanjun Wu China 8 225 1.3× 221 1.4× 61 2.7× 19 1.0× 40 2.4× 18 350
Saad Khan United Kingdom 5 157 0.9× 111 0.7× 46 2.0× 37 1.9× 13 0.8× 7 263
Ilana Traynis United States 6 213 1.2× 218 1.4× 17 0.7× 16 0.8× 23 1.4× 13 323
Alisa T. Thavikulwat United States 9 139 0.8× 144 0.9× 15 0.7× 25 1.3× 26 1.5× 30 208
Hironobu Tampo Japan 8 318 1.8× 293 1.9× 36 1.6× 25 1.3× 19 1.1× 28 432
Renu P. Rajan India 8 288 1.6× 248 1.6× 24 1.0× 21 1.1× 11 0.6× 31 397
Ying-Chun Jheng Taiwan 11 192 1.1× 125 0.8× 10 0.4× 41 2.2× 13 0.8× 23 345
Arielle Spitze United States 6 189 1.1× 189 1.2× 12 0.5× 9 0.5× 25 1.5× 11 295
Ryan T. Yanagihara United States 11 339 1.9× 387 2.5× 88 3.8× 32 1.7× 47 2.8× 22 516

Countries citing papers authored by Robbert Struyven

Since Specialization
Citations

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

Fields of papers citing papers by Robbert Struyven

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robbert Struyven

This figure shows the co-authorship network connecting the top 25 collaborators of Robbert Struyven. A scholar is included among the top collaborators of Robbert Struyven 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 Robbert Struyven. Robbert Struyven 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.
Chen, Chong, Liqin Wang, Xinyi Ding, et al.. (2025). Longitudinal Evaluation of Microvascular Changes and Imaging Biomarkers Associated with Visual Prognosis in Retinal Artery Occlusion. American Journal of Ophthalmology. 281. 312–325.
2.
Merle, David A., Robyn H. Guymer, Mark A. Chia, et al.. (2025). Mapping the impact: AI-driven quantification of geographic atrophy on OCT scans and its association with visual sensitivity loss. British Journal of Ophthalmology. 109(10). 1187–1193.
3.
Wagner, Siegfried K., Robbert Struyven, Zihan Sun, et al.. (2024). Retinal morphology across the menstrual cycle: insights from the UK Biobank. SHILAP Revista de lepidopterología. 2(1). 38–38. 1 indexed citations
4.
Williamson, Dominic J., Robbert Struyven, Fares Antaki, et al.. (2024). Artificial Intelligence to Facilitate Clinical Trial Recruitment in Age-Related Macular Degeneration. Ophthalmology Science. 4(6). 100566–100566. 6 indexed citations
5.
Moraes, Gabriella, Robbert Struyven, Siegfried K. Wagner, et al.. (2024). Quantifying Changes on OCT in Eyes Receiving Treatment for Neovascular Age-Related Macular Degeneration. SHILAP Revista de lepidopterología. 4(6). 100570–100570. 4 indexed citations
6.
Costanza, Enrico, et al.. (2024). Diagnostic decisions of specialist optometrists exposed to ambiguous deep-learning outputs. Scientific Reports. 14(1). 6775–6775. 2 indexed citations
7.
Korot, Edward, Josef Huemer, Hagar Khalid, et al.. (2023). Clinician-Driven AI: Code-Free Self-Training on Public Data for Diabetic Retinopathy Referral. JAMA Ophthalmology. 141(11). 1029–1029. 7 indexed citations
8.
Wagner, Siegfried K., Mario Cortina‐Borja, Josef Huemer, et al.. (2023). Determinants of non-attendance at face-to-face and telemedicine ophthalmic consultations. British Journal of Ophthalmology. 108(4). bjo–2022. 5 indexed citations
9.
Fu, Dun Jack, Gabriella Moraes, Konstantinos Balaskas, et al.. (2022). Evaluating an automated machine learning model that predicts visual acuity outcomes in patients with neovascular age-related macular degeneration. Graefe s Archive for Clinical and Experimental Ophthalmology. 260(8). 2461–2473. 19 indexed citations
10.
Wagner, Siegfried K., Fintan Hughes, Mario Cortina‐Borja, et al.. (2022). AlzEye: longitudinal record-level linkage of ophthalmic imaging and hospital admissions of 353 157 patients in London, UK. BMJ Open. 12(3). e058552–e058552. 20 indexed citations
11.
Balaskas, Konstantinos, Tiarnán D L Keenan, Livia Faes, et al.. (2022). Prediction of visual function from automatically quantified optical coherence tomography biomarkers in patients with geographic atrophy using machine learning. Scientific Reports. 12(1). 15565–15565. 16 indexed citations
12.
Zhou, Yukun, Siegfried K. Wagner, Mark A. Chia, et al.. (2022). AutoMorph: Automated Retinal Vascular Morphology Quantification Via a Deep Learning Pipeline. Translational Vision Science & Technology. 11(7). 12–12. 54 indexed citations
13.
Korot, Edward, Siegfried K. Wagner, Robbert Struyven, et al.. (2021). Investigating the impact of saliency maps on clinician’s confidence in model predictions. Investigative Ophthalmology & Visual Science. 62(8). 2297–2297. 1 indexed citations
14.
Wagner, Siegfried K., et al.. (2021). Using the What-if Tool to perform nearest counterfactual analysis on an AutoML model that predicts visual acuity outcomes in patients receiving treatment for wet age-related macular degeneration. Investigative Ophthalmology & Visual Science. 62(8). 291–291. 2 indexed citations
15.
Korot, Edward, et al.. (2021). Exploring the What-If-Tool as a solution for machine learning explainability in clinical practice. Investigative Ophthalmology & Visual Science. 62(8). 79–79. 1 indexed citations
16.
Zhang, Gongyu, Dun Jack Fu, Bart Liefers, et al.. (2021). Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study. The Lancet Digital Health. 3(10). e665–e675. 60 indexed citations
17.
Korot, Edward, et al.. (2021). Clinician-driven artificial intelligence in ophthalmology: resources enabling democratization. Current Opinion in Ophthalmology. 32(5). 445–451. 8 indexed citations
18.
Korot, Edward, Nikolas Pontikos, Faye Drawnel, et al.. (2021). Enablers and Barriers to Deployment of Smartphone-Based Home Vision Monitoring in Clinical Practice Settings. JAMA Ophthalmology. 140(2). 153–153. 21 indexed citations
19.
Peters, Jurriaan M., Robbert Struyven, Anna K. Prohl, et al.. (2019). White matter mean diffusivity correlates with myelination in tuberous sclerosis complex. Annals of Clinical and Translational Neurology. 6(7). 1178–1190. 21 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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