Robert Reihs
Impact in
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- Cancer Genomics and Diagnostics
Papers in
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- Biomedical Text Mining and Ontologies 7
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- AI in cancer detection 5
- Machine Learning in Healthcare 2
- Co-authors
- Heimo Müller (17 shared papers)Kurt Zatloukal (14 shared papers)Petr Holub (5 shared papers)David van Enckevort (3 shared papers)Morris A. Swertz (2 shared papers)Jan‐Eric Litton (1 shared paper)Andreas Holzinger (5 shared papers)David F. Steiner (3 shared papers)
- Journals
- Biopreservation and Biobanking (3 papers)BMC Bioinformatics (1 paper)European Journal of Human Genetics (1 paper)JAMA Network Open (1 paper)New Biotechnology (1 paper)
- Partner nations
- AustriaUnited StatesGermany
In The Last Decade
Robert Reihs
21 papers receiving 257 citations
Peers
Comparison fields: 5 of 72
- Health Informatics 9
- Cancer Research 36
- Public Health, Environmental and Occupational Health 65
- Artificial Intelligence 60
- Information Systems and Management 11
Countries citing papers authored by Robert Reihs
This map shows the geographic impact of Robert Reihs'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 Robert Reihs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Reihs more than expected).
Fields of papers citing papers by Robert Reihs
This network shows the impact of papers produced by Robert Reihs. 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 Robert Reihs. The network helps show where Robert Reihs may publish in the future.
Co-authors
The 25 scholars most cited alongside Robert Reihs, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 64 | |
| 2 | 2023 | 36 | |
| 3 | 2017 | 32 | |
| 4 | 2014 | 24 | |
| 5 | 2020 | 17 | |
| 6 | 2023 | 13 | |
| 7 | 2016 | 13 | |
| 8 | 2017 | 10 | |
| 9 | 2021 | 9 | |
| 10 | 2021 | 6 | |
| 11 | 2016 | 6 | |
| 12 | 2011 | 6 | |
| 13 | 2017 | 4 | |
| 14 | 2009 | 4 | |
| 15 | 2019 | 4 | |
| 16 | 2016 | 2 | |
| 17 | 2023 | 2 | |
| 18 | 2019 | 2 | |
| 19 | 2019 | 2 | |
| 20 | 2019 | 2 |
About Robert Reihs
Robert Reihs is a scholar working on Molecular Biology, Artificial Intelligence, Public Health, Environmental and Occupational Health, Computer Vision and Pattern Recognition and Information Systems and Management, having authored 21 papers that have together received 259 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (7 papers), Ethics in Clinical Research (5 papers), AI in cancer detection (5 papers), Data Visualization and Analytics (3 papers), Scientific Computing and Data Management (3 papers), Genomics and Rare Diseases (2 papers), Machine Learning in Healthcare (2 papers) and Multimedia Communication and Technology (2 papers). The work is most often cited by research in Health Informatics (9 citations), Cancer Research (36 citations), Public Health, Environmental and Occupational Health (65 citations), Artificial Intelligence (60 citations) and Information Systems and Management (11 citations). Robert Reihs has collaborated with scholars based in Austria, United States and Germany. Frequent co-authors include Heimo Müller, Kurt Zatloukal, Petr Holub, David van Enckevort, Morris A. Swertz, Jan‐Eric Litton, Andreas Holzinger, David F. Steiner, Greg S. Corrado and Lily H. Peng. Their work appears in journals such as Biopreservation and Biobanking, BMC Bioinformatics, European Journal of Human Genetics, JAMA Network Open and New Biotechnology.
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.