Markus Plass
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 5%
- AI in cancer detection
- Explainable Artificial Intelligence (XAI)
- Machine Learning in Healthcare
Papers in
-
- AI in cancer detection 7
- Explainable Artificial Intelligence (XAI) 3
- Artificial Intelligence in Games 2
-
- Artificial Intelligence in Healthcare and Education 8
- Co-authors
- Farid Moinfar (1 shared paper)Stephan Jahn (1 shared paper)Andreas Holzinger (9 shared papers)Heimo Müller (18 shared papers)Michaela Kargl (7 shared papers)Vasile Palade (1 shared paper)Michael Kickmeier-Rust (2 shared papers)Katharina Holzinger (1 shared paper)
In The Last Decade
Markus Plass
22 papers receiving 747 citations
Peers
Comparison fields: 5 of 119
- Health Informatics 136
- Artificial Intelligence 395
- Biophysics 47
- Radiology, Nuclear Medicine and Imaging 149
- Health Information Management 21
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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 209 | |
| 2 | 2018 | 148 | |
| 3 | 2022 | 86 | |
| 4 | 2022 | 56 | |
| 5 | 2022 | 56 | |
| 6 | 2023 | 53 | |
| 7 | 2023 | 36 | |
| 8 | 2024 | 23 | |
| 9 | 2023 | 18 | |
| 10 | 2022 | 15 | |
| 11 | 2023 | 13 | |
| 12 | 2024 | 11 | |
| 13 | 2022 | 10 | |
| 14 | 2022 | 10 | |
| 15 | 2024 | 7 | |
| 16 | 2023 | 6 | |
| 17 | 2023 | 5 | |
| 18 | 2025 | 3 | |
| 19 | 2022 | 2 | |
| 20 | 2023 | 2 |
About Markus Plass
Markus Plass is a scholar working on Artificial Intelligence, Health Informatics, Information Systems, Information Systems and Management and Radiology, Nuclear Medicine and Imaging, having authored 24 papers that have together received 772 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (8 papers), AI in cancer detection (7 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Scientific Computing and Data Management (4 papers), Research Data Management Practices (4 papers), Cell Image Analysis Techniques (3 papers), Explainable Artificial Intelligence (XAI) (3 papers) and Artificial Intelligence in Games (2 papers). The work is most often cited by research in Health Informatics (136 citations), Artificial Intelligence (395 citations), Biophysics (47 citations), Radiology, Nuclear Medicine and Imaging (149 citations) and Health Information Management (21 citations). Markus Plass has collaborated with scholars based in Austria, Germany and Italy. Frequent co-authors include Farid Moinfar, Stephan Jahn, Andreas Holzinger, Heimo Müller, Michaela Kargl, Vasile Palade, Michael Kickmeier-Rust, Katharina Holzinger, Camelia-M. Pintea and Gloria Cerasela Crişan. Their work appears in journals such as New Biotechnology, Nature Communications, Engineering Applications of Artificial Intelligence, Artificial Intelligence in Medicine and Applied Intelligence.
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.