S. Benson

35.7k total citations
13 papers, 414 citations indexed

About

S. Benson is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, S. Benson has authored 13 papers receiving a total of 414 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Radiology, Nuclear Medicine and Imaging, 3 papers in Pulmonary and Respiratory Medicine and 3 papers in Oncology. Recurrent topics in S. Benson's work include Radiomics and Machine Learning in Medical Imaging (8 papers), Colorectal Cancer Screening and Detection (3 papers) and Particle physics theoretical and experimental studies (2 papers). S. Benson is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (8 papers), Colorectal Cancer Screening and Detection (3 papers) and Particle physics theoretical and experimental studies (2 papers). S. Benson collaborates with scholars based in Netherlands, Denmark and United States. S. Benson's co-authors include Branka Marinović, Nancy A. Black, Evangelos K. Oikonomou, Folkert W. Asselbergs, Phyllis Thangaraj, Rohan Khera, Geerard L. Beets, Regina G. H. Beets‐Tan, John Williams and Doenja M. J. Lambregts and has published in prestigious journals such as European Heart Journal, Marine Ecology Progress Series and Computer Physics Communications.

In The Last Decade

S. Benson

11 papers receiving 395 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S. Benson Netherlands 6 287 175 159 83 42 13 414
P. Herranz Spain 9 62 0.2× 56 0.3× 56 0.4× 167 2.0× 14 0.3× 16 434
Dmitri Boutov Portugal 10 121 0.4× 198 1.1× 132 0.8× 70 0.8× 24 0.6× 13 344
Christopher J. Hintz United States 8 151 0.5× 126 0.7× 33 0.2× 160 1.9× 4 0.1× 15 322
Line Hermannsen Denmark 7 326 1.1× 234 1.3× 64 0.4× 87 1.0× 14 0.3× 12 368
CS Davis United States 10 150 0.5× 359 2.1× 280 1.8× 34 0.4× 103 2.5× 11 553
Sang‐Jong Park South Korea 12 43 0.1× 37 0.2× 183 1.2× 199 2.4× 5 0.1× 47 385
Giorgio Bolzon Italy 12 73 0.3× 282 1.6× 138 0.9× 49 0.6× 6 0.1× 17 411
В. В. Иванов Russia 6 112 0.4× 94 0.5× 206 1.3× 24 0.3× 133 3.2× 11 357
Andy Harris United States 8 367 1.3× 349 2.0× 369 2.3× 173 2.1× 28 0.7× 10 571
Atsushi Fujimura United States 11 170 0.6× 278 1.6× 99 0.6× 35 0.4× 21 0.5× 25 349

Countries citing papers authored by S. Benson

Since Specialization
Citations

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

Fields of papers citing papers by S. Benson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. Benson

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

All Works

13 of 13 papers shown
1.
Lambregts, Doenja M. J., et al.. (2024). An automated deep learning pipeline for EMVI classification and response prediction of rectal cancer using baseline MRI: a multi-centre study. npj Precision Oncology. 8(1). 17–17. 8 indexed citations
2.
Thangaraj, Phyllis, S. Benson, Evangelos K. Oikonomou, Folkert W. Asselbergs, & Rohan Khera. (2024). Cardiovascular care with digital twin technology in the era of generative artificial intelligence. European Heart Journal. 45(45). 4808–4821. 37 indexed citations
3.
Bodalal, Zuhir, et al.. (2024). Generalizability, robustness, and correction bias of segmentations of thoracic organs at risk in CT images. European Radiology. 35(7). 4335–4346.
4.
Griethuysen, Joost J. M. van, Doenja M. J. Lambregts, Renaud Tissier, et al.. (2024). Multi-sequence MRI radiomics of colorectal liver metastases: Which features are reproducible across readers?. European Journal of Radiology. 172. 111346–111346. 3 indexed citations
5.
Benson, S., et al.. (2024). Diagnostic performance of ADC and ADCratio in MRI-based prostate cancer assessment: A systematic review and meta-analysis. European Radiology. 35(1). 404–416. 2 indexed citations
6.
Nederend, Joost, Karin Horsthuis, Regina G. H. Beets‐Tan, et al.. (2023). A Deep Learning Framework with Explainability for the Prediction of Lateral Locoregional Recurrences in Rectal Cancer Patients with Suspicious Lateral Lymph Nodes. Diagnostics. 13(19). 3099–3099. 4 indexed citations
7.
Staal, Frank J. T., Mateus de Oliveira Taveira, Elisabeth G. Klompenhouwer, et al.. (2023). Independent validation of CT radiomics models in colorectal liver metastases: predicting local tumour progression after ablation. European Radiology. 34(6). 3635–3643. 5 indexed citations
8.
Haak, Hester E., Monique Maas, S. Benson, et al.. (2021). The use of deep learning on endoscopic images to assess the response of rectal cancer after chemoradiation. Surgical Endoscopy. 36(5). 3592–3600. 10 indexed citations
9.
Beets‐Tan, Regina G. H., et al.. (2021). An improved automatic system for aiding the detection of colon polyps using deep learning. Research Publications (Maastricht University). 32. 1–4. 1 indexed citations
10.
Benson, S. & K. Gizdov. (2019). NNDrone: A toolkit for the mass application of machine learning in High Energy Physics. Computer Physics Communications. 240. 15–20. 1 indexed citations
11.
Benson, S., et al.. (2015). The LHCb Turbo Stream. Journal of Physics Conference Series. 664(8). 82004–82004. 9 indexed citations
12.
Benson, S.. (2012). Mixing and CP Violation in the B System. CERN Bulletin.
13.
Marinović, Branka, et al.. (2005). From wind to whales: trophic links in a coastal upwelling system. Marine Ecology Progress Series. 289. 117–130. 334 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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