Rüdiger Schmitz
- Artificial Intelligence top 10%
- Oncology
- Radiology, Nuclear Medicine and Imaging
- Computer Vision and Pattern Recognition
- Epidemiology
- Co-authors
- René WernerFrederic MadestaAlexander SchlaeferThilo SentkerHelge KniepIvo M. BaltruschatNils GessertThomas Rösch
- Topics
- Radiomics and Machine Learning in Medical Imaging (4 papers)Gastric Cancer Management and Outcomes (4 papers)AI in cancer detection (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaGastroenterologyPLoS ONE
- Partner nations
- GermanySwitzerlandUnited States
In The Last Decade
Rüdiger Schmitz
21 papers receiving 296 citations
Peers
Comparison fields: 5 of 63
- Artificial Intelligence 157
- Oncology 135
- Radiology, Nuclear Medicine and Imaging 72
- Computer Vision and Pattern Recognition 54
- Epidemiology 53
Countries citing papers authored by Rüdiger Schmitz
This map shows the geographic impact of Rüdiger Schmitz'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 Rüdiger Schmitz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rüdiger Schmitz more than expected).
Fields of papers citing papers by Rüdiger Schmitz
This network shows the impact of papers produced by Rüdiger Schmitz. 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 Rüdiger Schmitz. The network helps show where Rüdiger Schmitz may publish in the future.
Co-authorship network of co-authors of Rüdiger Schmitz
This figure shows the co-authorship network connecting the top 25 collaborators of Rüdiger Schmitz. A scholar is included among the top collaborators of Rüdiger Schmitz 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 Rüdiger Schmitz. Rüdiger Schmitz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 12 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 70 | |
| 6 | 9 | |
| 7 | Abstract: Widening the Focus - Biomedical Image Segmentation Challenges and the Underestimated Role of Patch Sampling and Inference Strategies. | 1 |
| 8 | 2 | |
| 9 | 4 | |
| 10 | 1 | |
| 11 | 4 | |
| 12 | 7 | |
| 13 | 9 | |
| 14 | 2 | |
| 15 | 6 | |
| 16 | 2 | |
| 17 | 41 | |
| 18 | FAULT IDENTIFICATION IN ACCELERATOR CONTROL | 0 |
| 19 | 1 | |
| 20 | 2 |
About Rüdiger Schmitz
Rüdiger Schmitz is a scholar working on Structural Biology, Radiation and Modeling and Simulation, having authored 22 papers that have together received 302 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (4 papers), Gastric Cancer Management and Outcomes (4 papers) and AI in cancer detection (3 papers). The work is most often cited by research in Health Informatics (7 citations), Oncology (135 citations) and Artificial Intelligence (157 citations). Rüdiger Schmitz has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include René Werner, Frederic Madesta, Alexander Schlaefer, Thilo Sentker, Helge Kniep, Ivo M. Baltruschat, Nils Gessert, Thomas Rösch, Jenny Krause and Lushuai Cao. Their work appears in journals such as SHILAP Revista de lepidopterología, Gastroenterology and PLoS ONE.
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.