Rupert Ecker
Impact in
- Biophysics top 1%
- Cell Image Analysis Techniques
- Oncology top 5%
- Cutaneous Melanoma Detection and Management
Papers in
- Biophysics 14
- Cell Image Analysis Techniques 13
- Advanced Fluorescence Microscopy Techniques 3
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- AI in cancer detection 11
- Co-authors
- Amirreza Mahbod (12 shared papers)Gerald Schaefer (9 shared papers)Isabella Ellinger (13 shared papers)Chunliang Wang (5 shared papers)Georg Steiner (7 shared papers)Georg Dorffner (5 shared papers)Georg Stingl (4 shared papers)Alain Pitiot (1 shared paper)
- Journals
- Cytometry Part A (5 papers)Computer Methods and Programs in Biomedicine (2 papers)Blood (1 paper)Journal of Leukocyte Biology (1 paper)Journal of Pharmacology and Experimental Therapeutics (1 paper)
- Partner nations
- AustriaUnited KingdomAustralia
In The Last Decade
Rupert Ecker
42 papers receiving 2.2k citations
Peers
Comparison fields: 5 of 138
- Biophysics 267
- Oncology 809
- Dermatology 208
- Urology 135
- Artificial Intelligence 620
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 44 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 279 | |
| 2 | 2020 | 227 | |
| 3 | 2019 | 208 | |
| 4 | 2018 | 198 | |
| 5 | 2003 | 163 | |
| 6 | 2004 | 91 | |
| 7 | 2020 | 90 | |
| 8 | 2004 | 83 | |
| 9 | 2021 | 81 | |
| 10 | 2005 | 77 | |
| 11 | 2001 | 70 | |
| 12 | 2004 | 68 | |
| 13 | 2005 | 62 | |
| 14 | 2004 | 60 | |
| 15 | 2000 | 52 | |
| 16 | 2003 | 42 | |
| 17 | 2005 | 42 | |
| 18 | 2022 | 39 | |
| 19 | 2006 | 38 | |
| 20 | 2018 | 30 |
About Rupert Ecker
Rupert Ecker is a scholar working on Biophysics, Artificial Intelligence, Molecular Biology, Computer Vision and Pattern Recognition and Oncology, having authored 44 papers that have together received 2.3k indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (13 papers), AI in cancer detection (11 papers), Digital Imaging for Blood Diseases (7 papers), Cutaneous Melanoma Detection and Management (4 papers), Cancer Genomics and Diagnostics (3 papers), Dermatology and Skin Diseases (3 papers), Single-cell and spatial transcriptomics (3 papers) and Advanced Fluorescence Microscopy Techniques (3 papers). The work is most often cited by research in Biophysics (267 citations), Oncology (809 citations), Dermatology (208 citations), Urology (135 citations) and Artificial Intelligence (620 citations). Rupert Ecker has collaborated with scholars based in Austria, United Kingdom and Australia. Frequent co-authors include Amirreza Mahbod, Gerald Schaefer, Isabella Ellinger, Chunliang Wang, Georg Steiner, Georg Dorffner, Georg Stingl, Alain Pitiot, Adelheid Elbe‐Bürger and Michael Marberger. Their work appears in journals such as Cytometry Part A, Computer Methods and Programs in Biomedicine, Blood, Journal of Leukocyte Biology 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.