Irena Spasić
- Molecular Biology top 5%
- Artificial Intelligence top 1%
- Spectroscopy top 5%
- Biomedical Engineering
- Information Systems top 5%
- Co-authors
- Goran NenadićSophia AnaniadouDouglas B. KellWarwick B. DunnJohn KeaneMarie BrownPadraig CorcoranStephen G. Oliver
- Topics
- Biomedical Text Mining and Ontologies (38 papers)Natural Language Processing Techniques (23 papers)Topic Modeling (20 papers)
- Journals
- SHILAP Revista de lepidopterologíaBioinformaticsPLoS ONE
- Partner nations
- United KingdomJapanUnited States
In The Last Decade
Irena Spasić
91 papers receiving 2.6k citations
Peers
Comparison fields: 5 of 187
- Molecular Biology 1.5k
- Artificial Intelligence 1.1k
- Spectroscopy 279
- Biomedical Engineering 164
- Information Systems 139
Countries citing papers authored by Irena Spasić
This map shows the geographic impact of Irena Spasić'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 Irena Spasić with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Irena Spasić more than expected).
Fields of papers citing papers by Irena Spasić
This network shows the impact of papers produced by Irena Spasić. 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 Irena Spasić. The network helps show where Irena Spasić may publish in the future.
Co-authorship network of co-authors of Irena Spasić
This figure shows the co-authorship network connecting the top 25 collaborators of Irena Spasić. A scholar is included among the top collaborators of Irena Spasić 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 Irena Spasić. Irena Spasić 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 | 1 | |
| 3 | 15 | |
| 4 | 16 | |
| 5 | 206 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 8 | |
| 9 | 13 | |
| 10 | 37 | |
| 11 | 25 | |
| 12 | 10 | |
| 13 | 25 | |
| 14 | 51 | |
| 15 | 30 | |
| 16 | 28 | |
| 17 | 6 | |
| 18 | Selecting Features for Text- based Classification: from Documents to Terms | 1 |
| 19 | Tuning Context Features with Genetic Algorithms | 2 |
| 20 | Automatic Acronym Acquisition and Term Variation Management within Domain-Specific Texts * | 25 |
About Irena Spasić
Irena Spasić is a scholar working on Artificial Intelligence, Health Informatics and Language and Linguistics, having authored 97 papers that have together received 2.8k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (38 papers), Natural Language Processing Techniques (23 papers) and Topic Modeling (20 papers). The work is most often cited by research in Health Informatics (84 citations), Artificial Intelligence (1.1k citations) and Health Information Management (135 citations) Irena Spasić has collaborated with scholars based in United Kingdom, Japan and United States. Frequent co-authors include Goran Nenadić, Sophia Ananiadou, Douglas B. Kell, Warwick B. Dunn, John Keane, Marie Brown, Padraig Corcoran, Stephen G. Oliver, Hazel M. Davey and Amit Kumar. Their work appears in journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.
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.