Markus Plass
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 5%
- AI in cancer detection
- Explainable Artificial Intelligence (XAI)
- Machine Learning in Healthcare
Papers in
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- Artificial Intelligence in Healthcare and Education 10
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- AI in cancer detection 7
- Explainable Artificial Intelligence (XAI) 5
- Machine Learning and Data Classification 3
- Co-authors
- Andreas Holzinger (13 shared papers)Stephan Wenzel Jahn (1 shared paper)Farid Moinfar (1 shared paper)Heimo Müller (20 shared papers)Camelia-M. Pintea (3 shared papers)Vasile Palade (3 shared papers)Gloria Cerasela Crişan (3 shared papers)Katharina Holzinger (3 shared papers)
In The Last Decade
Markus Plass
26 papers receiving 976 citations
Peers
Comparison fields: 5 of 131
- Health Informatics 171
- Artificial Intelligence 537
- Biophysics 49
- Radiology, Nuclear Medicine and Imaging 173
- Health Information Management 27
Countries citing papers authored by Markus Plass
This map shows the geographic impact of Markus Plass'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 Markus Plass with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Plass more than expected).
Fields of papers citing papers by Markus Plass
This network shows the impact of papers produced by Markus Plass. 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 Markus Plass. The network helps show where Markus Plass may publish in the future.
Co-authors
The 25 scholars most cited alongside Markus Plass, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 239 | |
| 2 | 2018 | 180 | |
| 3 | 2022 | 97 | |
| 4 | 2016 | 79 | |
| 5 | 2023 | 66 | |
| 6 | 2022 | 66 | |
| 7 | 2022 | 64 | |
| 8 | 2023 | 41 | |
| 9 | 2024 | 30 | |
| 10 | 2019 | 24 | |
| 11 | 2023 | 23 | |
| 12 | 2022 | 23 | |
| 13 | 2023 | 18 | |
| 14 | 2024 | 12 | |
| 15 | 2024 | 10 | |
| 16 | 2022 | 9 | |
| 17 | 2023 | 7 | |
| 18 | 2023 | 7 | |
| 19 | 2023 | 6 | |
| 20 | 2025 | 4 |
About Markus Plass
Markus Plass is a scholar working on Health Informatics, Artificial Intelligence, Information Systems and Management, Biophysics and Radiology, Nuclear Medicine and Imaging, having authored 27 papers that have together received 1.0k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (10 papers), AI in cancer detection (7 papers), Explainable Artificial Intelligence (XAI) (5 papers), Machine Learning and Data Classification (3 papers), Research Data Management Practices (3 papers), Scientific Computing and Data Management (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Biomedical Text Mining and Ontologies (2 papers). The work is most often cited by research in Health Informatics (171 citations), Artificial Intelligence (537 citations), Biophysics (49 citations), Radiology, Nuclear Medicine and Imaging (173 citations) and Health Information Management (27 citations). Markus Plass has collaborated with scholars based in Austria, Germany and Italy. Frequent co-authors include Andreas Holzinger, Stephan Wenzel Jahn, Farid Moinfar, Heimo Müller, Camelia-M. Pintea, Vasile Palade, Gloria Cerasela Crişan, Katharina Holzinger, Michaela Kargl and Michael Kickmeier-Rust. Their work appears in journals such as New Biotechnology, The Journal of Pathology Clinical Research, IEEE Access, Yearbook of Medical Informatics and JAMA Network Open.
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.