Anneloes E. Bohte

1.6k total citations · 1 hit paper
15 papers, 1.3k citations indexed

About

Anneloes E. Bohte is a scholar working on Epidemiology, Hepatology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Anneloes E. Bohte has authored 15 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Epidemiology, 6 papers in Hepatology and 4 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Anneloes E. Bohte's work include Liver Disease Diagnosis and Treatment (12 papers), Diet, Metabolism, and Disease (4 papers) and Lysosomal Storage Disorders Research (3 papers). Anneloes E. Bohte is often cited by papers focused on Liver Disease Diagnosis and Treatment (12 papers), Diet, Metabolism, and Disease (4 papers) and Lysosomal Storage Disorders Research (3 papers). Anneloes E. Bohte collaborates with scholars based in Netherlands, France and Japan. Anneloes E. Bohte's co-authors include Jaap Stoker, Jochem R. van Werven, Shandra Bipat, Aart J. Nederveen, Peter L. M. Jansen, Patrick Asbach, Jayant A. Talwalkar, David J. Lomas, Utaroh Motosugi and Siddharth Singh and has published in prestigious journals such as PLoS ONE, Radiology and The American Journal of Gastroenterology.

In The Last Decade

Anneloes E. Bohte

15 papers receiving 1.3k citations

Hit Papers

Diagnostic Performance of Magnetic Resonance Elastography... 2014 2026 2018 2022 2014 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anneloes E. Bohte Netherlands 12 1.1k 645 240 216 160 15 1.3k
Brandon Ang United States 8 1.3k 1.2× 774 1.2× 357 1.5× 184 0.9× 135 0.8× 10 1.4k
William Haufe United States 11 936 0.9× 553 0.9× 301 1.3× 142 0.7× 113 0.7× 14 1.0k
Ethan Sy United States 12 1.5k 1.4× 912 1.4× 386 1.6× 137 0.6× 194 1.2× 16 1.6k
Magdy Elkashab Canada 10 944 0.9× 686 1.1× 161 0.7× 70 0.3× 109 0.7× 18 1.0k
Young Eun Chon South Korea 21 1.2k 1.1× 1.1k 1.6× 110 0.5× 53 0.2× 206 1.3× 76 1.5k
Hidekatsu Kuroda Japan 18 597 0.6× 574 0.9× 48 0.2× 107 0.5× 142 0.9× 82 890
Kyu Sik Jung South Korea 22 1.4k 1.3× 1.2k 1.8× 130 0.5× 44 0.2× 189 1.2× 36 1.7k
Y K Tse Hong Kong 13 667 0.6× 391 0.6× 170 0.7× 26 0.1× 236 1.5× 23 990
Shunya Nakashita Japan 9 337 0.3× 189 0.3× 81 0.3× 94 0.4× 184 1.1× 19 669

Countries citing papers authored by Anneloes E. Bohte

Since Specialization
Citations

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

Fields of papers citing papers by Anneloes E. Bohte

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anneloes E. Bohte. 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 Anneloes E. Bohte. The network helps show where Anneloes E. Bohte may publish in the future.

Co-authorship network of co-authors of Anneloes E. Bohte

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

All Works

15 of 15 papers shown
1.
Draijer, Laura G., Anneloes E. Bohte, Tammo H. Pels Rijcken, et al.. (2019). Comparison of diagnostic accuracy of screening tests ALT and ultrasound for pediatric non-alcoholic fatty liver disease. European Journal of Pediatrics. 178(6). 863–870. 51 indexed citations
2.
Bohte, Anneloes E., et al.. (2017). Iron storage in liver, bone marrow and splenic Gaucheroma reflects residual disease in type 1 Gaucher disease patients on treatment. British Journal of Haematology. 179(4). 635–647. 23 indexed citations
3.
Bohte, Anneloes E., et al.. (2016). Imaging characteristics of focal splenic and hepatic lesions in type 1 Gaucher disease. Blood Cells Molecules and Diseases. 60. 49–57. 23 indexed citations
4.
Koot, Bart G.P., Eric de Groot, Olga H. van der Baan‐Slootweg, et al.. (2015). Nonalcoholic fatty liver disease and cardiovascular risk in children with obesity. Obesity. 23(6). 1239–1243. 16 indexed citations
5.
Singh, Siddharth, Sudhakar K. Venkatesh, Zhen Wang, et al.. (2014). Diagnostic Performance of Magnetic Resonance Elastography in Staging Liver Fibrosis: A Systematic Review and Meta-analysis of Individual Participant Data. Clinical Gastroenterology and Hepatology. 13(3). 440–451.e6. 414 indexed citations breakdown →
6.
Singh, Siddharth, Sudhakar K. Venkatesh, Zhen Wang, et al.. (2014). Diagnostic Performance of Magnetic Resonance Elastography for the Staging of Liver Fibrosis: A Systematic Review and Collaborative Individual Participant Data Meta-Analysis. The American Journal of Gastroenterology. 109. S144–S144. 1 indexed citations
7.
Bohte, Anneloes E., Philippe Garteiser, A. de Niet, et al.. (2013). MR Elastography of the Liver: Defining Thresholds for Detecting Viscoelastic Changes. Radiology. 269(3). 768–776. 31 indexed citations
8.
Bohte, Anneloes E., Laura van Dussen, Erik M. Akkerman, et al.. (2013). Liver Fibrosis in Type I Gaucher Disease: Magnetic Resonance Imaging, Transient Elastography and Parameters of Iron Storage. PLoS ONE. 8(3). e57507–e57507. 48 indexed citations
9.
Bohte, Anneloes E., A. de Niet, Louis Jansen, et al.. (2013). Non-invasive evaluation of liver fibrosis: a comparison of ultrasound-based transient elastography and MR elastography in patients with viral hepatitis B and C. European Radiology. 24(3). 638–648. 76 indexed citations
10.
Koot, Bart G.P., Olga H. van der Baan‐Slootweg, Anneloes E. Bohte, et al.. (2013). Accuracy of prediction scores and novel biomarkers for predicting nonalcoholic fatty liver disease in obese children. Obesity. 21(3). 583–590. 64 indexed citations
11.
Runge, Jurgen H., Anneloes E. Bohte, Joanne Verheij, et al.. (2013). Comparison of interobserver agreement of magnetic resonance elastography with histopathological staging of liver fibrosis. Abdominal Imaging. 39(2). 283–290. 35 indexed citations
12.
Bohte, Anneloes E., Philippe Garteiser, A. de Niet, et al.. (2013). MR Elastography of the Liver: Defining Thresholds for Detecting Viscoelastic Changes. Radiology. 122669–122669. 3 indexed citations
13.
Bohte, Anneloes E., Bart G.P. Koot, Olga H. van der Baan‐Slootweg, et al.. (2011). US Cannot Be Used to Predict the Presence or Severity of Hepatic Steatosis in Severely Obese Adolescents. Radiology. 262(1). 327–334. 59 indexed citations
14.
Bohte, Anneloes E., Aart J. Nederveen, & Jaap Stoker. (2011). Hepatic fat-content assessment using magnetic resonance-based methods. Imaging in Medicine. 3(2). 193–206. 3 indexed citations
15.
Bohte, Anneloes E., Jochem R. van Werven, Shandra Bipat, & Jaap Stoker. (2010). The diagnostic accuracy of US, CT, MRI and 1H-MRS for the evaluation of hepatic steatosis compared with liver biopsy: a meta-analysis. European Radiology. 21(1). 87–97. 417 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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