Karin Verspoor
- Health Informatics top 0.5%
- Artificial Intelligence top 0.5%
- Topic Modeling 79
- Natural Language Processing Techniques 60
- Semantic Web and Ontologies 35
- Machine Learning in Healthcare 20
- Molecular Biology top 5%
- Biomedical Text Mining and Ontologies 116
- Bioinformatics and Genomic Networks 33
- Machine Learning in Bioinformatics 20
- Genomics and Phylogenetic Studies 17
- Co-authors
- Timothy BaldwinLawrence HunterKevin Bretonnel CohenWilliam A. BaumgartnerFernando Martín-SánchezJustin ZobelHaibin LiuStephen Wan
- Journals
- BMC Bioinformatics (15 papers)Database (10 papers)Journal of Biomedical Informatics (10 papers)
- Partner nations
- AustraliaUnited StatesUnited Kingdom
In The Last Decade
Karin Verspoor
232 papers receiving 3.6k citations
Peers
Comparison fields: 5 of 174
- Health Informatics 179
- Artificial Intelligence 2.1k
- Health Information Management 162
- Applied Microbiology and Biotechnology 54
- Molecular Biology 1.8k
Countries citing papers authored by Karin Verspoor
This map shows the geographic impact of Karin Verspoor'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 Karin Verspoor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karin Verspoor more than expected).
Fields of papers citing papers by Karin Verspoor
This network shows the impact of papers produced by Karin Verspoor. 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 Karin Verspoor. The network helps show where Karin Verspoor may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Karin Verspoor, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 8 | |
| 4 | 2024 | 1 | |
| 5 | 2023 | 2 | |
| 6 | 2023 | 4 | |
| 7 | 2023 | 1 | |
| 8 | 2023 | 4 | |
| 9 | 2023 | 9 | |
| 10 | 2022 | 2 | |
| 11 | 2022 | 1 | |
| 12 | 2020 | 3 | |
| 13 | Detecting Chemical Reactions in Patents | 2019 | 3 |
| 14 | 2019 | 19 | |
| 15 | Findings of the WMT 2018 Biomedical Translation Shared Task: Evaluation on Medline test sets | 2018 | 0 |
| 16 | 2017 | 121 | |
| 17 | 2016 | 11 | |
| 18 | Simple similarity-based question answering strategies for biomedical text | 2012 | 4 |
| 19 | 1998 | 77 | |
| 20 | 1998 | 24 |
About Karin Verspoor
Karin Verspoor is a scholar working on Health Informatics, Artificial Intelligence and Issues, ethics and legal aspects, having authored 246 papers that have together received 3.8k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (116 papers), Topic Modeling (79 papers), Natural Language Processing Techniques (60 papers), Semantic Web and Ontologies (35 papers), Bioinformatics and Genomic Networks (33 papers), Machine Learning in Bioinformatics (20 papers), Machine Learning in Healthcare (20 papers) and Genomics and Phylogenetic Studies (17 papers). The work is most often cited by research in Health Informatics (179 citations), Artificial Intelligence (2.1k citations) and Health Information Management (162 citations). Karin Verspoor has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include Timothy Baldwin, Lawrence Hunter, Kevin Bretonnel Cohen, William A. Baumgartner, Fernando Martín-Sánchez, Justin Zobel, Haibin Liu, Stephen Wan, Doris Hoogeveen and Christophe Roeder. Their work appears in journals such as BMC Bioinformatics, Database, Journal of Biomedical Informatics, Journal of Biomedical Semantics and Bioinformatics.
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.