Mark ter Laan

2.2k total citations
50 papers, 1.3k citations indexed

About

Mark ter Laan is a scholar working on Genetics, Neurology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Mark ter Laan has authored 50 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Genetics, 15 papers in Neurology and 15 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Mark ter Laan's work include Glioma Diagnosis and Treatment (21 papers), Radiomics and Machine Learning in Medical Imaging (10 papers) and Meningioma and schwannoma management (9 papers). Mark ter Laan is often cited by papers focused on Glioma Diagnosis and Treatment (21 papers), Radiomics and Machine Learning in Medical Imaging (10 papers) and Meningioma and schwannoma management (9 papers). Mark ter Laan collaborates with scholars based in Netherlands, United States and Germany. Mark ter Laan's co-authors include Pieter Wesseling, William P. J. Leenders, Krissie Lenting, J. Marc C. van Dijk, Roel G.W. Verhaak, Gosse J. Adema, Barbara M. Schulte, Esther D. Kers‐Rebel, Paul R. Gielen and Kiek Verrijp and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and The FASEB Journal.

In The Last Decade

Mark ter Laan

48 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark ter Laan Netherlands 18 375 245 240 221 216 50 1.3k
David Kaul Germany 19 258 0.7× 235 1.0× 178 0.7× 111 0.5× 158 0.7× 102 1.3k
Niloufar Sadeghi Belgium 19 355 0.9× 171 0.7× 487 2.0× 136 0.6× 327 1.5× 69 1.5k
Amadé Bregy United States 24 652 1.7× 79 0.3× 366 1.5× 195 0.9× 410 1.9× 53 1.7k
Marian C. Neidert Switzerland 22 599 1.6× 389 1.6× 485 2.0× 95 0.4× 315 1.5× 108 1.8k
Jordan Xu United States 8 597 1.6× 75 0.3× 257 1.1× 88 0.4× 319 1.5× 22 1.3k
Wai Hoe Ng Singapore 27 648 1.7× 144 0.6× 504 2.1× 264 1.2× 609 2.8× 115 2.3k
Ricardo J. Komotar United States 19 587 1.6× 77 0.3× 464 1.9× 118 0.5× 202 0.9× 79 1.4k
M. R. Garcia de Eulate Spain 13 245 0.7× 138 0.6× 181 0.8× 124 0.6× 88 0.4× 29 883
Pedro David Delgado‐López Spain 16 412 1.1× 56 0.2× 269 1.1× 123 0.6× 311 1.4× 66 1.3k
Walter C. Jean United States 24 216 0.6× 247 1.0× 619 2.6× 195 0.9× 306 1.4× 102 2.0k

Countries citing papers authored by Mark ter Laan

Since Specialization
Citations

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

Fields of papers citing papers by Mark ter Laan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark ter Laan. 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 Mark ter Laan. The network helps show where Mark ter Laan may publish in the future.

Co-authorship network of co-authors of Mark ter Laan

This figure shows the co-authorship network connecting the top 25 collaborators of Mark ter Laan. A scholar is included among the top collaborators of Mark ter Laan 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 Mark ter Laan. Mark ter Laan 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.
Hannink, Gerjon, Hilko Ardon, Rutger K. Balvers, et al.. (2025). Between-hospital variation in biopsy indication for patients with newly diagnosed glioblastoma in the Dutch Quality Registry for Neurosurgery. Journal of Neuro-Oncology. 172(3). 625–632. 1 indexed citations
2.
Cornelissen, Lenneke A. M., et al.. (2024). Glioma-Associated Sialoglycans Drive the Immune Suppressive Phenotype and Function of Myeloid Cells. Pharmaceutics. 16(7). 953–953. 3 indexed citations
3.
Laan, Mark ter, Yasin Temel, Sjoert Pegge, et al.. (2023). Subclassification of the Koos grade 2 vestibular schwannoma into 2a and 2b for individualized patient care: A validity and reliability study. European Journal of Radiology. 162. 110799–110799. 1 indexed citations
4.
Rovers, Maroeska M., et al.. (2023). Stereotactic laser ablation in neuro-oncology - A survey among European neurosurgeons. SHILAP Revista de lepidopterología. 3. 101749–101749.
5.
6.
Henssen, Dylan, Frederick J. A. Meijer, Anja G. van der Kolk, et al.. (2023). Head-To-Head Comparison of PET and Perfusion Weighted MRI Techniques to Distinguish Treatment Related Abnormalities from Tumor Progression in Glioma. Cancers. 15(9). 2631–2631. 5 indexed citations
7.
8.
Laan, Mark ter, et al.. (2022). The role and effectiveness of augmented reality in patient education: A systematic review of the literature. Patient Education and Counseling. 105(7). 1917–1927. 44 indexed citations
9.
Overduin, Christiaan G., et al.. (2021). Laser Interstitial Thermal Therapy in Patients with Newly Diagnosed Glioblastoma: A Systematic Review. Journal of Clinical Medicine. 10(2). 355–355. 12 indexed citations
10.
11.
Laan, Mark ter, et al.. (2020). Reducing the burden of brain tumor surgery. Acta Neurochirurgica. 163(7). 1879–1882. 2 indexed citations
12.
Piai, Vitória, et al.. (2020). Information Recall in Pre-Operative Consultation for Glioma Surgery Using Actual Size Three-Dimensional Models. Journal of Clinical Medicine. 9(11). 3660–3660. 15 indexed citations
13.
Lenting, Krissie, Remco C. de Boer, Elizabeth A. Tindall, et al.. (2019). Mapping actionable pathways and mutations in brain tumours using targeted RNA next generation sequencing. Acta Neuropathologica Communications. 7(1). 185–185. 6 indexed citations
14.
Laan, Mark ter, et al.. (2019). Selective Intensive Care Unit Admission After Adult Supratentorial Tumor Craniotomy: Complications, Length of Stay, and Costs. Neurosurgery. 86(1). E54–E59. 26 indexed citations
15.
Santegoets, Kim C. M., Paul R. Gielen, Christian Büll, et al.. (2019). Expression profiling of immune inhibitory Siglecs and their ligands in patients with glioma. Cancer Immunology Immunotherapy. 68(6). 937–949. 35 indexed citations
16.
Maal, Thomas, et al.. (2017). Single-Step Resection of an Intraosseous Meningioma and Cranial Reconstruction: Technical Note. World Neurosurgery. 108. 225–229. 22 indexed citations
17.
Gielen, Paul R., Barbara M. Schulte, Esther D. Kers‐Rebel, et al.. (2016). Elevated levels of polymorphonuclear myeloid-derived suppressor cells in patients with glioblastoma highly express S100A8/9 and arginase and suppress T cell function. Neuro-Oncology. 18(9). 1253–1264. 127 indexed citations
18.
Laan, Mark ter, et al.. (2011). Electrical modulation of the sympathetic nervous system in order to augment cerebral blood flow: a protocol for an experimental study. BMJ Open. 1(1). e000120–e000120. 5 indexed citations
19.
Dijk, J. Marc C. van, et al.. (2011). Surgical clipping as the preferred treatment for aneurysms of the middle cerebral artery. Acta Neurochirurgica. 153(11). 2111–2117. 61 indexed citations
20.
Laan, Mark ter & J.J.A. Mooij. (2005). Improvement after treatment of hydrocephalus in aneurysmal subarachnoid haemorrhage: implications for grading and prognosis. Acta Neurochirurgica. 148(3). 325–328. 6 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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