David Rauber
Impact in
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- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
Papers in
- Surgery 8
- Esophageal Cancer Research and Treatment 4
- Helicobacter pylori-related gastroenterology studies 2
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- Advanced Neural Network Applications 4
- Advanced Image and Video Retrieval Techniques 2
- Co-authors
- Christoph Palm (15 shared papers)Robert Mendel (11 shared papers)Luis A. de Souza (5 shared papers)João Paulo Papa (5 shared papers)Matthias W. Beckmann (1 shared paper)PA Fasching (1 shared paper)S. Ackermann (1 shared paper)Grit Mehlhorn (1 shared paper)
- Journals
- Endoscopy (4 papers)European Journal of Obstetrics & Gynecology and Reproductive Biology (1 paper)Computers in Biology and Medicine (1 paper)Scientific Reports (1 paper)Gut (1 paper)
- Partner nations
- GermanyBrazilUnited States
In The Last Decade
David Rauber
14 papers receiving 205 citations
Peers
Comparison fields: 5 of 46
- Health Informatics 7
- Computer Vision and Pattern Recognition 70
- Artificial Intelligence 63
- Radiology, Nuclear Medicine and Imaging 31
- Surgery 51
Countries citing papers authored by David Rauber
This map shows the geographic impact of David Rauber'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 David Rauber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Rauber more than expected).
Fields of papers citing papers by David Rauber
This network shows the impact of papers produced by David Rauber. 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 David Rauber. The network helps show where David Rauber may publish in the future.
Co-authors
The 25 scholars most cited alongside David Rauber, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 82 | |
| 2 | 2008 | 33 | |
| 3 | 2022 | 24 | |
| 4 | 2024 | 21 | |
| 5 | 2023 | 15 | |
| 6 | 2022 | 14 | |
| 7 | 2019 | 9 | |
| 8 | 2025 | 5 | |
| 9 | 2018 | 2 | |
| 10 | 2024 | 1 | |
| 11 | 2021 | 1 | |
| 12 | 2021 | 1 | |
| 13 | 2022 | 1 | |
| 14 | 2021 | 1 | |
| 15 | 2025 | 0 | |
| 16 | 2025 | 0 | |
| 17 | 2025 | 0 | |
| 18 | 2025 | 0 |
About David Rauber
David Rauber is a scholar working on Surgery, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, Oncology and Artificial Intelligence, having authored 18 papers that have together received 210 indexed citations. Recurring topics across this work include Colorectal Cancer Screening and Detection (4 papers), Advanced Neural Network Applications (4 papers), Esophageal Cancer Research and Treatment (4 papers), AI in cancer detection (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Brain Tumor Detection and Classification (2 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Helicobacter pylori-related gastroenterology studies (2 papers). The work is most often cited by research in Health Informatics (7 citations), Computer Vision and Pattern Recognition (70 citations), Artificial Intelligence (63 citations), Radiology, Nuclear Medicine and Imaging (31 citations) and Surgery (51 citations). David Rauber has collaborated with scholars based in Germany, Brazil and United States. Frequent co-authors include Christoph Palm, Robert Mendel, Luis A. de Souza, João Paulo Papa, Matthias W. Beckmann, PA Fasching, S. Ackermann, Grit Mehlhorn, Christoph Römmele and Alanna Ebigbo. Their work appears in journals such as Endoscopy, European Journal of Obstetrics & Gynecology and Reproductive Biology, Computers in Biology and Medicine, Scientific Reports and Gut.
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.