Marcel Wiesweg

2.7k total citations
47 papers, 461 citations indexed

About

Marcel Wiesweg is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Molecular Biology. According to data from OpenAlex, Marcel Wiesweg has authored 47 papers receiving a total of 461 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Pulmonary and Respiratory Medicine, 32 papers in Oncology and 12 papers in Molecular Biology. Recurrent topics in Marcel Wiesweg's work include Lung Cancer Treatments and Mutations (25 papers), Lung Cancer Diagnosis and Treatment (11 papers) and Cancer Genomics and Diagnostics (9 papers). Marcel Wiesweg is often cited by papers focused on Lung Cancer Treatments and Mutations (25 papers), Lung Cancer Diagnosis and Treatment (11 papers) and Cancer Genomics and Diagnostics (9 papers). Marcel Wiesweg collaborates with scholars based in Germany, United States and Austria. Marcel Wiesweg's co-authors include Martin Schüler, Kaid Darwiche, Clemens Aigner, Martin Metzenmacher, Kurt Werner Schmid, Wilfried Eberhardt, Henning Reis, Martin Stuschke, Brigitte Schumacher and Stefan Kasper and has published in prestigious journals such as Journal of Clinical Oncology, Oncogene and Scientific Reports.

In The Last Decade

Marcel Wiesweg

42 papers receiving 457 citations

Peers

Marcel Wiesweg
G. Riely United States
Greg Dyson United States
Martin Metzenmacher Germany
Joanna Niemiec Poland
Andrew Erickson Finland
Itai Pashtan United States
Wen‐Ze Qiu China
Antonia Márquez Spain
Gennaro Palmiotti Italy
Patrick Lebok Germany
G. Riely United States
Marcel Wiesweg
Citations per year, relative to Marcel Wiesweg Marcel Wiesweg (= 1×) peers G. Riely

Countries citing papers authored by Marcel Wiesweg

Since Specialization
Citations

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

Fields of papers citing papers by Marcel Wiesweg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marcel Wiesweg

This figure shows the co-authorship network connecting the top 25 collaborators of Marcel Wiesweg. A scholar is included among the top collaborators of Marcel Wiesweg 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 Marcel Wiesweg. Marcel Wiesweg 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.
Schüler, Martin, J. Hense, Kaid Darwiche, et al.. (2024). Early Metabolic Response by PET Predicts Sensitivity to Next-Line Targeted Therapy inEGFR-Mutated Lung Cancer with Unknown Mechanism of Acquired Resistance. Journal of Nuclear Medicine. 65(6). 851–855. 3 indexed citations
2.
Guberina, Maja, Christoph Pöttgen, Nika Guberina, et al.. (2024). Long-Term Survival in Patients with Oligometastatic Non-Small Cell Lung Cancer by a Multimodality Treatment—Comparison with Stage III Disease. Cancers. 16(6). 1174–1174. 3 indexed citations
3.
Wiesweg, Marcel, Stefan Kasper, Tobias Herold, et al.. (2023). Smaller panel, similar results: genomic profiling and molecularly informed therapy in pancreatic cancer. ESMO Open. 8(3). 101539–101539. 6 indexed citations
4.
5.
Evers, Georg, Daniel C. Christoph, Wolfgang M. Brueckl, et al.. (2023). 1300P Treatment and clinical outcome in recurrent/refractory locally advanced NSCLC following chemoradiotherapy and consolidative durvalumab. Annals of Oncology. 34. S749–S749.
6.
7.
Wiesweg, Marcel, Sebastian Bauer, Anja Welt, et al.. (2023). Electronic Patient-Reported Outcome Measures (ePROMs) Improve the Assessment of Underrated Physical and Psychological Symptom Burden among Oncological Inpatients. Cancers. 15(11). 3029–3029. 7 indexed citations
8.
Keyl, Julius, René Hosch, Simon Bogner, et al.. (2022). Deep learning‐based assessment of body composition and liver tumour burden for survival modelling in advanced colorectal cancer. Journal of Cachexia Sarcopenia and Muscle. 14(1). 545–552. 19 indexed citations
9.
Guberina, Maja, Ken Herrmann, Christoph Pöttgen, et al.. (2022). Prediction of malignant lymph nodes in NSCLC by machine-learning classifiers using EBUS-TBNA and PET/CT. Scientific Reports. 12(1). 17511–17511. 13 indexed citations
10.
Keyl, Julius, Stefan Kasper, Marcel Wiesweg, et al.. (2022). Multimodal survival prediction in advanced pancreatic cancer using machine learning. ESMO Open. 7(5). 100555–100555. 27 indexed citations
11.
Darwiche, Kaid, Michał Seweryn, Vedat Yildiz, et al.. (2021). DNA methylation of PTGER4 in peripheral blood plasma helps to distinguish between lung cancer, benign pulmonary nodules and chronic obstructive pulmonary disease patients. European Journal of Cancer. 147. 142–150. 24 indexed citations
12.
Wiesweg, Marcel, Martin Metzenmacher, Wilfried Eberhardt, et al.. (2021). BRAF mutations and BRAF mutation functional class have no negative impact on the clinical outcome of advanced NSCLC and associate with susceptibility to immunotherapy. European Journal of Cancer. 149. 211–221. 12 indexed citations
13.
Wiesweg, Marcel, Fabian Mairinger, Henning Reis, et al.. (2020). Machine learning reveals a PD-L1–independent prediction of response to immunotherapy of non-small cell lung cancer by gene expression context. European Journal of Cancer. 140. 76–85. 37 indexed citations
14.
Metzenmacher, Martin, Renáta Váraljai, Balázs Hegedűs, et al.. (2020). Plasma Next Generation Sequencing and Droplet Digital-qPCR-Based Quantification of Circulating Cell-Free RNA for Noninvasive Early Detection of Cancer. Cancers. 12(2). 353–353. 29 indexed citations
15.
Ting, Saskia, Henning Reis, Martin Metzenmacher, et al.. (2020). ERK phosphorylation as a marker of RAS activity and its prognostic value in non-small cell lung cancer. Lung Cancer. 149. 10–16. 9 indexed citations
16.
Paul, A., Kurt Werner Schmid, P. M. Markus, et al.. (2020). Combined systemic inflammation score (SIS) correlates with prognosis in patients with advanced pancreatic cancer receiving palliative chemotherapy. Journal of Cancer Research and Clinical Oncology. 147(2). 579–591. 18 indexed citations
17.
Welt, Anja, Simon Bogner, Marina Arendt, et al.. (2020). Improved survival in metastatic breast cancer: results from a 20-year study involving 1033 women treated at a single comprehensive cancer center. Journal of Cancer Research and Clinical Oncology. 146(6). 1559–1566. 15 indexed citations
18.
Wiesweg, Marcel, Thomas Herold, Martin Metzenmacher, et al.. (2019). Clinical response to crizotinib and emergence of resistance in lung adenocarcinoma harboring a MET c-Cbl binding site mutation. Lung Cancer. 139. 165–168. 4 indexed citations
19.
Wiesweg, Marcel, Fabian Mairinger, Henning Reis, et al.. (2019). Machine learning-based predictors for immune checkpoint inhibitor therapy of non-small-cell lung cancer. Annals of Oncology. 30(4). 655–657. 23 indexed citations
20.
Wiesweg, Marcel, Henning Reis, Moritz Goetz, et al.. (2018). Phosphorylation of p70 Ribosomal Protein S6 Kinase β-1 is an Independent Prognostic Parameter in Metastatic Colorectal Cancer. Clinical Colorectal Cancer. 17(2). e331–e352. 10 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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