Markus Kreuzthaler
- Artificial Intelligence top 10%
- Molecular Biology
- Computer Vision and Pattern Recognition top 10%
- Health Information Management top 5%
- Electrical and Electronic Engineering
- Co-authors
- Stefan SchulzMarkus QuaritschBernhard RinnerHorst BischofAlexandra Pomares QuimbayaAndrea BergholdAlexander AvianPhilipp Daumke
- Topics
- Biomedical Text Mining and Ontologies (26 papers)Topic Modeling (16 papers)Natural Language Processing Techniques (15 papers)
- Partner nations
- AustriaGermanySwitzerland
In The Last Decade
Markus Kreuzthaler
31 papers receiving 289 citations
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 155
- Molecular Biology 107
- Computer Vision and Pattern Recognition 79
- Health Information Management 49
- Electrical and Electronic Engineering 32
Countries citing papers authored by Markus Kreuzthaler
This map shows the geographic impact of Markus Kreuzthaler'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 Kreuzthaler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Kreuzthaler more than expected).
Fields of papers citing papers by Markus Kreuzthaler
This network shows the impact of papers produced by Markus Kreuzthaler. 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 Kreuzthaler. The network helps show where Markus Kreuzthaler may publish in the future.
Co-authorship network of co-authors of Markus Kreuzthaler
This figure shows the co-authorship network connecting the top 25 collaborators of Markus Kreuzthaler. A scholar is included among the top collaborators of Markus Kreuzthaler based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Markus Kreuzthaler. Markus Kreuzthaler is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 4 | |
| 4 | 5 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 4 | |
| 9 | 2 | |
| 10 | 2 | |
| 11 | 5 | |
| 12 | 0 | |
| 13 | 1 | |
| 14 | 35 | |
| 15 | 4 | |
| 16 | 45 | |
| 17 | 0 | |
| 18 | Unsupervised Abbreviation Detection in Clinical Narratives. | 9 |
| 19 | 23 | |
| 20 | 3 |
About Markus Kreuzthaler
Markus Kreuzthaler is a scholar working on Health Informatics, Artificial Intelligence and Health Information Management, having authored 40 papers that have together received 303 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (26 papers), Topic Modeling (16 papers) and Natural Language Processing Techniques (15 papers). The work is most often cited by research in Health Information Management (49 citations), Health Informatics (13 citations) and Artificial Intelligence (155 citations). Markus Kreuzthaler has collaborated with scholars based in Austria, Germany and Switzerland. Frequent co-authors include Stefan Schulz, Markus Quaritsch, Bernhard Rinner, Horst Bischof, Alexandra Pomares Quimbaya, Andrea Berghold, Stefan Schulz, Alexander Avian, Philipp Daumke and Peter K. Kaiser. Their work appears in journals such as Bioinformatics, Scientific Reports and IEEE Access.
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.