Erik Ranschaert

2.4k total citations
36 papers, 1.4k citations indexed

About

Erik Ranschaert is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics and Artificial Intelligence. According to data from OpenAlex, Erik Ranschaert has authored 36 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Radiology, Nuclear Medicine and Imaging, 16 papers in Health Informatics and 8 papers in Artificial Intelligence. Recurrent topics in Erik Ranschaert's work include Artificial Intelligence in Healthcare and Education (16 papers), Radiology practices and education (13 papers) and Radiomics and Machine Learning in Medical Imaging (7 papers). Erik Ranschaert is often cited by papers focused on Artificial Intelligence in Healthcare and Education (16 papers), Radiology practices and education (13 papers) and Radiomics and Machine Learning in Medical Imaging (7 papers). Erik Ranschaert collaborates with scholars based in Netherlands, Belgium and United States. Erik Ranschaert's co-authors include Charisma Hehakaya, Ellen H.M. Moors, Wouter Boon, Mohammad Hosein Rezazade Mehrizi, J. Raymond Geis, Elmar Kotter, Jack Spencer, William Shields, Jacob L. Jaremko and Carol C. Wu and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Erik Ranschaert

35 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Erik Ranschaert Netherlands 18 819 751 298 251 121 36 1.4k
Nabile Safdar United States 20 777 0.9× 583 0.8× 254 0.9× 341 1.4× 83 0.7× 78 1.7k
Seth J. Berkowitz United States 14 705 0.9× 391 0.5× 626 2.1× 80 0.3× 65 0.5× 29 1.4k
Viknesh Sounderajah United Kingdom 18 337 0.4× 228 0.3× 248 0.8× 124 0.5× 143 1.2× 62 1.6k
Himel Mondal India 18 348 0.4× 663 0.9× 307 1.0× 57 0.2× 137 1.1× 197 1.4k
Danton Char United States 13 368 0.4× 771 1.0× 382 1.3× 160 0.6× 126 1.0× 45 1.6k
Thomas Huang United States 6 535 0.7× 1.1k 1.5× 412 1.4× 74 0.3× 91 0.8× 13 1.4k
Nada Alsuhebany Saudi Arabia 7 283 0.3× 618 0.8× 297 1.0× 111 0.4× 100 0.8× 25 1.4k
Bibb Allen United States 20 906 1.1× 536 0.7× 282 0.9× 251 1.0× 131 1.1× 67 1.4k
Sumaya N. Almohareb Saudi Arabia 4 271 0.3× 617 0.8× 294 1.0× 110 0.4× 92 0.8× 15 1.3k
Atheer Aldairem Saudi Arabia 3 271 0.3× 617 0.8× 294 1.0× 110 0.4× 92 0.8× 6 1.2k

Countries citing papers authored by Erik Ranschaert

Since Specialization
Citations

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

Fields of papers citing papers by Erik Ranschaert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Erik Ranschaert

This figure shows the co-authorship network connecting the top 25 collaborators of Erik Ranschaert. A scholar is included among the top collaborators of Erik Ranschaert 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 Erik Ranschaert. Erik Ranschaert 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
1.
Kyriazi, Stavroula, Susan C. Shelmerdine, Constantinus F. M. Buckens, et al.. (2025). Real-World Monitoring of Artificial Intelligence in Radiology: Challenges and Best Practices. Korean Journal of Radiology. 26(11). 1010–1010.
2.
Ranschaert, Erik, et al.. (2024). Artificial intelligence-assisted double reading of chest radiographs to detect clinically relevant missed findings: a two-centre evaluation. European Radiology. 34(9). 5876–5885. 6 indexed citations
3.
Ranschaert, Erik, et al.. (2023). Artificial Intelligence Tool for Detection and Worklist Prioritization Reduces Time to Diagnosis of Incidental Pulmonary Embolism at CT. Radiology Cardiothoracic Imaging. 5(2). e220163–e220163. 47 indexed citations
4.
Jiménez-Pastor, Ana, Jacob J. Visser, Merel Huisman, et al.. (2023). A deep learning-based application for COVID-19 diagnosis on CT: The Imaging COVID-19 AI initiative. PLoS ONE. 18(5). e0285121–e0285121. 6 indexed citations
5.
Ugga, Lorenzo, Renato Cuocolo, Deborah R. Shatzkes, et al.. (2022). Virtual conferences: results of an international survey on radiologist preferences and perspectives. European Radiology. 32(12). 8191–8199. 6 indexed citations
6.
Ranschaert, Erik, et al.. (2021). Optimization of Radiology Workflow with Artificial Intelligence. Radiologic Clinics of North America. 59(6). 955–966. 50 indexed citations
7.
Jacobs, Colin, Arnaud A. A. Setio, Ernst T. Scholten, et al.. (2021). Deep Learning for Lung Cancer Detection on Screening CT Scans: Results of a Large-Scale Public Competition and an Observer Study with 11 Radiologists. Radiology Artificial Intelligence. 3(6). e210027–e210027. 29 indexed citations
8.
Huisman, Merel, Erik Ranschaert, William Parker, et al.. (2021). An international survey on AI in radiology in 1,041 radiologists and radiology residents part 1: fear of replacement, knowledge, and attitude. European Radiology. 31(9). 7058–7066. 143 indexed citations
9.
Huisman, Merel, Erik Ranschaert, William Parker, et al.. (2021). An international survey on AI in radiology in 1041 radiologists and radiology residents part 2: expectations, hurdles to implementation, and education. European Radiology. 31(11). 8797–8806. 91 indexed citations
10.
Clarke, Christopher, et al.. (2020). Giving radiologists a voice: a review of podcasts in radiology. Insights into Imaging. 11(1). 33–33. 10 indexed citations
11.
Hehakaya, Charisma, et al.. (2020). Implementation of artificial intelligence (AI) applications in radiology: hindering and facilitating factors. European Radiology. 30(10). 5525–5532. 183 indexed citations
12.
Geis, J. Raymond, Adrian P. Brady, Carol C. Wu, et al.. (2019). Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement. Radiology. 293(2). 436–440. 206 indexed citations
13.
Geis, J. Raymond, Adrian P. Brady, Carol C. Wu, et al.. (2019). Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement. Journal of the American College of Radiology. 16(11). 1516–1521. 71 indexed citations
14.
Ranschaert, Erik, Peter M. A. van Ooijen, Geraldine McGinty, & Paul M. Parizel. (2016). Radiologists’ Usage of Social Media: Results of the RANSOM Survey. Journal of Digital Imaging. 29(4). 443–449. 64 indexed citations
15.
Ranschaert, Erik, et al.. (2015). Comparison of European (ESR) and American (ACR) White Papers on Teleradiology: Patient Primacy Is Paramount. Journal of the American College of Radiology. 12(2). 174–182. 9 indexed citations
16.
Ranschaert, Erik, et al.. (2015). Social media for radiologists: an introduction. Insights into Imaging. 6(6). 741–752. 32 indexed citations
17.
Ranschaert, Erik, et al.. (2012). European Teleradiology now and in the future: results of an online survey. Insights into Imaging. 4(1). 93–102. 37 indexed citations
18.
Arts, Rob, et al.. (2012). Small bowel leiomyosarcoma: A case report and literature review. The Turkish Journal of Gastroenterology. 23(4). 381–384. 9 indexed citations
19.
Ranschaert, Erik, et al.. (2000). Glossar. Der Radiologe. 40(4). 400–403. 1 indexed citations
20.
Stockx, L, et al.. (1997). Percutaneous hydrodynamic thrombectomy of acute thrombosis in transjugular intrahepatic portosystemic shunt (TIPS): A feasibility study in five patients. CardioVascular and Interventional Radiology. 20(3). 180–183. 9 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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