Rupert Ecker
Impact in
- Biophysics top 1%
- Cell Image Analysis Techniques
- Oncology top 5%
- Cutaneous Melanoma Detection and Management
Papers in
-
- AI in cancer detection 11
- Biophysics 11
- Cell Image Analysis Techniques 10
- Co-authors
- Amirreza Mahbod (9 shared papers)Gerald Schaefer (7 shared papers)Chunliang Wang (3 shared papers)Isabella Ellinger (8 shared papers)Georg Steiner (7 shared papers)Georg Dorffner (5 shared papers)Georg Stingl (4 shared papers)Adelheid Elbe‐Bürger (3 shared papers)
- Journals
- Cytometry Part A (5 papers)Computer Methods and Programs in Biomedicine (2 papers)Current Treatment Options in Oncology (1 paper)Clinical Cancer Research (1 paper)Journal of Pharmacology and Experimental Therapeutics (1 paper)
- Partner nations
- AustriaUnited KingdomAustralia
In The Last Decade
Rupert Ecker
34 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 131
- Biophysics 259
- Oncology 793
- Dermatology 216
- Urology 141
- Immunology and Allergy 116
Countries citing papers authored by Rupert Ecker
This map shows the geographic impact of Rupert Ecker'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 Rupert Ecker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rupert Ecker more than expected).
Fields of papers citing papers by Rupert Ecker
This network shows the impact of papers produced by Rupert Ecker. 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 Rupert Ecker. The network helps show where Rupert Ecker may publish in the future.
Co-authors
The 25 scholars most cited alongside Rupert Ecker, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 272 | |
| 2 | 2020 | 210 | |
| 3 | 2018 | 185 | |
| 4 | 2019 | 185 | |
| 5 | 2003 | 156 | |
| 6 | 2004 | 91 | |
| 7 | 2020 | 84 | |
| 8 | 2004 | 80 | |
| 9 | 2005 | 73 | |
| 10 | 2021 | 70 | |
| 11 | 2001 | 66 | |
| 12 | 2004 | 62 | |
| 13 | 2004 | 54 | |
| 14 | 2000 | 51 | |
| 15 | 2005 | 50 | |
| 16 | 2003 | 42 | |
| 17 | 2005 | 40 | |
| 18 | 2006 | 36 | |
| 19 | 2022 | 25 | |
| 20 | 2009 | 24 |
About Rupert Ecker
Rupert Ecker is a scholar working on Artificial Intelligence, Biophysics, Molecular Biology, Computer Vision and Pattern Recognition and Oncology, having authored 35 papers that have together received 2.0k indexed citations. Recurring topics across this work include AI in cancer detection (11 papers), Cell Image Analysis Techniques (10 papers), Cutaneous Melanoma Detection and Management (4 papers), Digital Imaging for Blood Diseases (4 papers), Single-cell and spatial transcriptomics (4 papers), Dermatology and Skin Diseases (3 papers), T-cell and B-cell Immunology (3 papers) and Immune Cell Function and Interaction (3 papers). The work is most often cited by research in Biophysics (259 citations), Oncology (793 citations), Dermatology (216 citations), Urology (141 citations) and Immunology and Allergy (116 citations). Rupert Ecker has collaborated with scholars based in Austria, United Kingdom and Australia. Frequent co-authors include Amirreza Mahbod, Gerald Schaefer, Chunliang Wang, Isabella Ellinger, Georg Steiner, Georg Dorffner, Georg Stingl, Adelheid Elbe‐Bürger, Gero Kramer and Alain Pitiot. Their work appears in journals such as Cytometry Part A, Computer Methods and Programs in Biomedicine, Current Treatment Options in Oncology, Clinical Cancer Research and Journal of Pharmacology and Experimental Therapeutics.
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.