Robbert Struyven

1.4k citations
19 papers · 248 · h-index 8

Impact in

    • Retinal Diseases and Treatments
    • Retinal and Optic Conditions
    • Glaucoma and retinal disorders
    • Artificial Intelligence in Healthcare and Education

Papers in

Robbert Struyven

17 papers receiving 245 citations

Peers

Robbert Struyven
Comparison fields: 5 of 55
  • Ophthalmology 157
  • Health Informatics 17
  • Radiology, Nuclear Medicine and Imaging 179
  • Health Information Management 7
  • Neurology 7
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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-authors

The 25 scholars most cited alongside Robbert Struyven, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Robbert Struyven Line = papers co-authored together Robbert Struyven links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 202160
2 202254
3 201921
4 202121
5 202220
6 202219
7 202216
8 20218
9 20237
10 20246
11 20235
12 20244
13
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
20212
14 20242
15 20241
16
Investigating the impact of saliency maps on clinician’s confidence in model predictions
20211
17
Exploring the What-If-Tool as a solution for machine learning explainability in clinical practice
20211
18 20250
19 20250

About Robbert Struyven

Robbert Struyven is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology, Health Informatics, Artificial Intelligence and Public Health, Environmental and Occupational Health, having authored 19 papers that have together received 248 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (14 papers), Retinal and Optic Conditions (11 papers), Retinal Diseases and Treatments (10 papers), Glaucoma and retinal disorders (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), COVID-19 diagnosis using AI (1 paper) and Artificial Intelligence in Healthcare (1 paper). The work is most often cited by research in Ophthalmology (157 citations), Health Informatics (17 citations), Radiology, Nuclear Medicine and Imaging (179 citations), Health Information Management (7 citations) and Neurology (7 citations). Robbert Struyven has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent co-authors include Pearse A. Keane, Siegfried K. Wagner, Konstantinos Balaskas, Dun Jack Fu, Nikolas Pontikos, Gongyu Zhang, Bart Liefers, Daniel C. Alexander, Livia Faes and Mark A. Chia. Their work appears in journals such as Investigative Ophthalmology & Visual Science, Scientific Reports, British Journal of Ophthalmology, JAMA Ophthalmology and Translational Vision Science & Technology.

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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