Péter Pollner
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Quantum chaos and dynamical systems
Papers in
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- Complex Network Analysis Techniques 10
- Opinion Dynamics and Social Influence 6
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- AI in cancer detection 5
- Co-authors
- Gergely Palla (14 shared papers)Tamás Vicsek (10 shared papers)Anna Horváth (8 shared papers)Illés J. Farkas (3 shared papers)Tamás Joó (8 shared papers)Imre Derényi (2 shared papers)Péter Banczerowski (7 shared papers)István Csabai (10 shared papers)
- Journals
- Scientific Reports (3 papers)PLoS ONE (3 papers)World Neurosurgery (2 papers)Physica A Statistical Mechanics and its Applications (2 papers)Scientific Data (2 papers)
- Partner nations
- HungaryUnited KingdomGermany
In The Last Decade
Péter Pollner
50 papers receiving 305 citations
Peers
Comparison fields: 5 of 95
- Statistical and Nonlinear Physics 101
- Health Informatics 5
- Genetics 27
- Health 20
- Rheumatology 34
Countries citing papers authored by Péter Pollner
This map shows the geographic impact of Péter Pollner'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 Péter Pollner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Péter Pollner more than expected).
Fields of papers citing papers by Péter Pollner
This network shows the impact of papers produced by Péter Pollner. 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 Péter Pollner. The network helps show where Péter Pollner may publish in the future.
Co-authors
The 25 scholars most cited alongside Péter Pollner, 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 54 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 34 | |
| 2 | 2008 | 33 | |
| 3 | 2015 | 21 | |
| 4 | 2022 | 18 | |
| 5 | 2021 | 18 | |
| 6 | 2013 | 17 | |
| 7 | 2018 | 15 | |
| 8 | 2022 | 12 | |
| 9 | 2025 | 10 | |
| 10 | 2018 | 9 | |
| 11 | 2018 | 9 | |
| 12 | 2008 | 8 | |
| 13 | 2019 | 7 | |
| 14 | 1996 | 7 | |
| 15 | 2016 | 7 | |
| 16 | 2003 | 6 | |
| 17 | 2017 | 6 | |
| 18 | 2021 | 5 | |
| 19 | 1999 | 5 | |
| 20 | 2016 | 5 |
About Péter Pollner
Péter Pollner is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Molecular Biology, Radiology, Nuclear Medicine and Imaging and Condensed Matter Physics, having authored 54 papers that have together received 311 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (10 papers), Theoretical and Computational Physics (6 papers), Opinion Dynamics and Social Influence (6 papers), AI in cancer detection (5 papers), Management of metastatic bone disease (5 papers), Bioinformatics and Genomic Networks (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Complex Systems and Time Series Analysis (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (101 citations), Health Informatics (5 citations), Genetics (27 citations), Health (20 citations) and Rheumatology (34 citations). Péter Pollner has collaborated with scholars based in Hungary, United Kingdom and Germany. Frequent co-authors include Gergely Palla, Tamás Vicsek, Anna Horváth, Illés J. Farkas, Tamás Joó, Imre Derényi, Péter Banczerowski, István Csabai, Katalin Molnár and György Surján. Their work appears in journals such as Scientific Reports, PLoS ONE, World Neurosurgery, Physica A Statistical Mechanics and its Applications and Scientific Data.
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.