Michael Sabel

15.2k total citations · 3 hit papers
184 papers, 9.3k citations indexed

About

Michael Sabel is a scholar working on Genetics, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Michael Sabel has authored 184 papers receiving a total of 9.3k indexed citations (citations by other indexed papers that have themselves been cited), including 134 papers in Genetics, 52 papers in Pulmonary and Respiratory Medicine and 52 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Michael Sabel's work include Glioma Diagnosis and Treatment (132 papers), Brain Metastases and Treatment (40 papers) and Meningioma and schwannoma management (40 papers). Michael Sabel is often cited by papers focused on Glioma Diagnosis and Treatment (132 papers), Brain Metastases and Treatment (40 papers) and Meningioma and schwannoma management (40 papers). Michael Sabel collaborates with scholars based in Germany, Switzerland and United States. Michael Sabel's co-authors include Guido Reifenberger, Marion Rapp, Jörg Felsberg, Karl‐Josef Langen, Gabriele Stoffels, Hans‐Jakob Steiger, Michael Weller, Walter Stummer, Marcel A. Kamp and Matthias Simon and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Michael Sabel

176 papers receiving 9.1k citations

Hit Papers

Temozolomide chemotherapy... 2007 2026 2013 2019 2012 2007 2009 250 500 750

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Michael Sabel 6.5k 2.6k 2.5k 2.1k 1.9k 184 9.3k
Eric T. Wong 4.9k 0.7× 1.9k 0.8× 2.4k 0.9× 1.8k 0.9× 1.2k 0.6× 157 8.3k
Dominique Figarella-Branger 7.1k 1.1× 2.2k 0.8× 2.1k 0.8× 3.2k 1.5× 2.2k 1.2× 13 11.6k
Andrew B. Lassman 5.8k 0.9× 2.0k 0.8× 3.0k 1.2× 1.9k 0.9× 1.5k 0.8× 191 8.8k
David R. Macdonald 8.1k 1.2× 2.8k 1.1× 3.2k 1.3× 1.8k 0.9× 1.7k 0.9× 77 9.7k
Ahmed Idbaïh 5.4k 0.8× 1.4k 0.6× 1.8k 0.7× 3.4k 1.7× 2.6k 1.4× 259 9.7k
Olivier Chinot 7.5k 1.1× 1.7k 0.7× 3.3k 1.3× 3.1k 1.5× 2.4k 1.2× 296 11.7k
Michael A. Vogelbaum 8.1k 1.2× 3.2k 1.2× 4.1k 1.6× 2.0k 1.0× 1.6k 0.9× 239 12.8k
Jörg Felsberg 6.1k 0.9× 1.3k 0.5× 2.1k 0.8× 3.2k 1.5× 2.6k 1.3× 94 8.0k
Yaning Chen 5.8k 0.9× 1.4k 0.5× 2.1k 0.8× 3.6k 1.7× 2.1k 1.1× 40 11.0k
P Farah 5.8k 0.9× 1.3k 0.5× 2.0k 0.8× 3.1k 1.5× 2.0k 1.1× 8 10.2k

Countries citing papers authored by Michael Sabel

Since Specialization
Citations

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

Fields of papers citing papers by Michael Sabel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Sabel

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Sabel. A scholar is included among the top collaborators of Michael Sabel 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 Michael Sabel. Michael Sabel 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.
Kisić, Alemka, et al.. (2025). Predicting Caregiver Anxiety and Depression From Patient Distress in Brain Tumor Dyads: Actor‐Partner Interdependence Model. Cancer Medicine. 14(19). e71271–e71271. 1 indexed citations
2.
Werner, Jan‐Michael, Jörg Steinbach, Michael Sabel, et al.. (2025). Functional connectivity between tumor region and resting-state networks as imaging biomarker for overall survival in recurrent gliomas diagnosed by O-(2-[18F]fluoroethyl)-l-tyrosine PET. Neuro-Oncology Advances. 7(1). vdaf023–vdaf023. 1 indexed citations
4.
Staub‐Bartelt, Franziska, et al.. (2024). Increased Distress in Neurooncological Patients, a Monocentric Longitudinal Study: When to Screen Which Patient?. SHILAP Revista de lepidopterología. 12(9). 217–217.
6.
Staub‐Bartelt, Franziska, Marion Rapp, & Michael Sabel. (2023). Resection of Eloquent Located Brain Tumors by Mapping Only—A Feasibility Study. Brain Sciences. 13(10). 1366–1366. 1 indexed citations
8.
Rapp, Marion, et al.. (2022). Would they do it again? Final treatment decisions in malignant brain tumour patients—a caregiver’s perspective. Supportive Care in Cancer. 30(5). 3985–3993. 2 indexed citations
9.
Kamp, Marcel A., et al.. (2021). Psychooncological distress in low-grade glioma patients—a monocentric study. Acta Neurochirurgica. 164(3). 713–722. 12 indexed citations
10.
Staub‐Bartelt, Franziska, et al.. (2021). Direct Cortical Stimulation in Neurosurgical Emergencies: Single-Center Experience in 2 Patients. World Neurosurgery. 150. 147–152. 1 indexed citations
11.
Koch, Katharina, Rudolf Hartmann, Abigail K. Suwala, et al.. (2021). Overexpression of Cystine/Glutamate Antiporter xCT Correlates with Nutrient Flexibility and ZEB1 Expression in Highly Clonogenic Glioblastoma Stem-like Cells (GSCs). Cancers. 13(23). 6001–6001. 12 indexed citations
12.
Fischer, Igor, Hendrik-Jan Mijderwijk, Ulf D. Kahlert, et al.. (2020). Association between health insurance status and malignant glioma. Neuro-Oncology Practice. 7(5). 531–540. 4 indexed citations
14.
Kamp, Marcel A., Maxine Dibué, Antonio Santacroce, et al.. (2016). ecancermedicalscience. ecancermedicalscience. 7. 306–306. 14 indexed citations
15.
Lohmann, Philipp, Gabriele Stoffels, Garry Ceccon, et al.. (2016). Radiation injury vs. recurrent brain metastasis: combining textural feature radiomics analysis and standard parameters may increase 18F-FET PET accuracy without dynamic scans. European Radiology. 27(7). 2916–2927. 74 indexed citations
16.
Ringel, Florian, Haiko Pape, Michael Sabel, et al.. (2015). Clinical benefit from resection of recurrent glioblastomas: results of a multicenter study including 503 patients with recurrent glioblastomas undergoing surgical resection. Neuro-Oncology. 18(1). 96–104. 184 indexed citations
17.
Wick, Wolfgang, Christoph Meisner, Bettina Hentschel, et al.. (2013). Prognostic or predictive value of MGMT promoter methylation in gliomas depends on IDH1 mutation. Neurology. 81(17). 1515–1522. 173 indexed citations
18.
Ernst, Aurélie, Stefanie Hofmann, Rezvan Ahmadi, et al.. (2009). Genomic and Expression Profiling of Glioblastoma Stem Cell–Like Spheroid Cultures Identifies Novel Tumor-Relevant Genes Associated with Survival. Clinical Cancer Research. 15(21). 6541–6550. 150 indexed citations
19.
Wick, Wolfgang, Christian Hartmann, Corinna Engel, et al.. (2009). NOA-04 Randomized Phase III Trial of Sequential Radiochemotherapy of Anaplastic Glioma With Procarbazine, Lomustine, and Vincristine or Temozolomide. Journal of Clinical Oncology. 27(35). 5874–5880. 571 indexed citations breakdown →
20.
Felsberg, Jörg, Marion Rapp, Simon Loeser, et al.. (2009). Prognostic Significance of Molecular Markers and Extent of Resection in Primary Glioblastoma Patients. Clinical Cancer Research. 15(21). 6683–6693. 153 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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