Martin Diebold

1.1k total citations
39 papers, 708 citations indexed

About

Martin Diebold is a scholar working on Pathology and Forensic Medicine, Immunology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Martin Diebold has authored 39 papers receiving a total of 708 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Pathology and Forensic Medicine, 11 papers in Immunology and 8 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Martin Diebold's work include Multiple Sclerosis Research Studies (9 papers), Glioma Diagnosis and Treatment (6 papers) and Neuroinflammation and Neurodegeneration Mechanisms (6 papers). Martin Diebold is often cited by papers focused on Multiple Sclerosis Research Studies (9 papers), Glioma Diagnosis and Treatment (6 papers) and Neuroinflammation and Neurodegeneration Mechanisms (6 papers). Martin Diebold collaborates with scholars based in Germany, Switzerland and France. Martin Diebold's co-authors include Tobias Derfuß, Nicholas Sanderson, Ludwig Kappos, Jens Kühle, Burkhard Becher, Edoardo Galli, Marco Prinz, Manfred Claassen, Raija L.P. Lindberg and Florian Ingelfinger and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Medicine.

In The Last Decade

Martin Diebold

37 papers receiving 697 citations

Peers

Martin Diebold

IMMUN

PFM

ONCOL

EPIDE

Lama Fawaz Canada

С. В. Лапин Russia

S. Bubel Germany

Ernesto Roldán Spain

Patricia Momigliano‐Richiardi Italy

Neil Minton United States

J. Link Sweden

Nicole Culbertson United States

Evi Regitz Germany

Nicolas Chamberlain United States

Lama Fawaz Canada

Martin Diebold

522 ×2.2

IMMUN

79 ×0.3

388 ×1.9

PFM

141 ×1.2

ONCOL

122 ×1.2

EPIDE

Citations per year, relative to Martin Diebold Martin Diebold (= 1×) peers Lama Fawaz

Countries citing papers authored by Martin Diebold

Since Specialization

Citations

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

Fields of papers citing papers by Martin Diebold

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Diebold

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

All Works

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20 of 20 papers shown

Rau, Alexander, Marco Reisert, L. E. Becker, et al.. (2025). Microstructural differentiation of cerebral metastases, glioblastoma, meningioma, and primary CNS lymphoma using advanced diffusion imaging techniques. Neuro-Oncology Advances. 7(1). vdaf076–vdaf076.

Diebold, Martin, L. E. Becker, Theo Demerath, et al.. (2025). Non-invasive Prediction of Meningioma Tumor Grade by Quantification of Shape-based Radiomics Features and Surface Regularity. Clinical Neuroradiology. 36(1). 169–176.

Diebold, Martin, Patrick Wuchter, Peter E. Huber, et al.. (2024). Effects of tumor treating fields (TTFields) on human mesenchymal stromal cells. Journal of Neuro-Oncology. 169(2). 329–340. 2 indexed citations

Süß, Patrick, Martin Diebold, & Roman Sankowski. (2024). Advances in understanding the immunity of the brain and its borders: Focus on brain macrophages. Clinical and Translational Medicine. 14(9). e70014–e70014. 2 indexed citations

Diebold, Martin, Mukesch Shah, Bastian Malzkorn, et al.. (2024). Freiburg Neuropathology Case Conference:. Clinical Neuroradiology. 34(1). 279–286. 1 indexed citations

Erny, Daniel, Alexander Rau, Jonas A. Hosp, et al.. (2023). Mesoscopic Assessment of Microstructure in Glioblastomas and Metastases by Merging Advanced Diffusion Imaging with Immunohistopathology. American Journal of Neuroradiology. 44(11). 1262–1269. 4 indexed citations

Callegari, Ilaria, Johanna Oechtering, Sylvain Perriot, et al.. (2023). Cell-binding IgM in CSF is distinctive of multiple sclerosis and targets the iron transporter SCARA5. Brain. 147(3). 839–848. 3 indexed citations

Diebold, Martin, et al.. (2023). How myeloid cells shape experimental autoimmune encephalomyelitis: At the crossroads of outside‐in immunity. European Journal of Immunology. 53(10). e2250234–e2250234. 5 indexed citations

Diebold, Martin, Daniel Erny, Jonas A. Hosp, et al.. (2022). Diffusion Microstructure Imaging to Analyze Perilesional T2 Signal Changes in Brain Metastases and Glioblastomas. Cancers. 14(5). 1155–1155. 14 indexed citations

10.

Jiao, Huipeng, Laurens Wachsmuth, Masahiro Nagata, et al.. (2022). ADAR1 averts fatal type I interferon induction by ZBP1. Nature. 607(7920). 776–783. 137 indexed citations

11.

Diebold, Martin, Marco Meola, Tim Roloff, et al.. (2022). Gut microbiota composition as a candidate risk factor for dimethyl fumarate-induced lymphopenia in multiple sclerosis. Gut Microbes. 14(1). 2147055–2147055. 16 indexed citations

12.

Diebold, Martin, Mukesch Shah, Marco Prinz, et al.. (2021). Freiburg Neuropathology Case Conference. Clinical Neuroradiology. 31(3). 885–892. 3 indexed citations

13.

Galli, Edoardo, Felix J. Hartmann, Bettina Schreiner, et al.. (2019). GM-CSF and CXCR4 define a T helper cell signature in multiple sclerosis. Nature Medicine. 25(8). 1290–1300. 135 indexed citations

14.

Diebold, Martin, Claudia Sievers, Glenn R. Bantug, et al.. (2017). Dimethyl fumarate influences innate and adaptive immunity in multiple sclerosis. Journal of Autoimmunity. 86. 39–50. 61 indexed citations

15.

Diebold, Martin & Tobias Derfuß. (2016). Immunological treatment of multiple sclerosis. Seminars in Hematology. 53. S54–S57. 15 indexed citations

16.

Brassart, Bertrand, Gaëtan Deslée, Jeanne‐Marie Perotin, et al.. (2015). A competitive enzyme-linked immunosorbent assay for quantification of tetrastatin in body fluids and tumor extracts. Analytical Biochemistry. 482. 16–21. 6 indexed citations

17.

McLennan, Stuart, et al.. (2014). Nurses’ perspectives regarding the disclosure of errors to patients: A qualitative study. International Journal of Nursing Studies. 54. 16–22. 31 indexed citations

18.

Delmas, Christelle, Fabien Vitry, Olivier Bouché, et al.. (2009). Increased risk of colonic neoplasia in patients with sporadic duodenal adenoma. Gastroentérologie Clinique et Biologique. 33(5). 441–445. 15 indexed citations

19.

Ladam-Marcus, V., et al.. (2006). Endométriomes de la paroi abdominale : apport de l’imagerie. Journal de Radiologie. 87(11). 1691–1695. 11 indexed citations

20.

Abdelli, Naceur, et al.. (1996). Endoscopic Retrograde Cholangiography in a Metastatic Melanoma of the Gallbladder Presenting as a Gallstone Migration. Endoscopy. 28(4). 402–402. 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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