Suzan Üsküdarlı
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Information Systems
- Molecular Biology
- Software top 10%
- Co-authors
- Tunga GüngörBurak AcarArzucan ÖzgürNadin KökciyanJiangbo DangRüştü TürkayJosé F. Aldana‐MontesMaría del Mar Roldán‐García
- Topics
- Topic Modeling (12 papers)Natural Language Processing Techniques (10 papers)Biomedical Text Mining and Ontologies (5 papers)
- Partner nations
- TürkiyeUnited StatesNetherlands
In The Last Decade
Suzan Üsküdarlı
32 papers receiving 157 citations
Peers
Comparison fields: 5 of 48
- Artificial Intelligence 127
- Computer Vision and Pattern Recognition 34
- Information Systems 32
- Molecular Biology 27
- Software 21
Countries citing papers authored by Suzan Üsküdarlı
This map shows the geographic impact of Suzan Üsküdarlı'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 Suzan Üsküdarlı with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suzan Üsküdarlı more than expected).
Fields of papers citing papers by Suzan Üsküdarlı
This network shows the impact of papers produced by Suzan Üsküdarlı. 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 Suzan Üsküdarlı. The network helps show where Suzan Üsküdarlı may publish in the future.
Co-authorship network of co-authors of Suzan Üsküdarlı
This figure shows the co-authorship network connecting the top 25 collaborators of Suzan Üsküdarlı. A scholar is included among the top collaborators of Suzan Üsküdarlı 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 Suzan Üsküdarlı. Suzan Üsküdarlı is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | 0 | |
| 6 | 4 | |
| 7 | 2 | |
| 8 | 5 | |
| 9 | 8 | |
| 10 | 15 | |
| 11 | 14 | |
| 12 | Overview of the ImageCLEF 2015 liver CT annotation task | 6 |
| 13 | ImageCLEF Liver CT Image Annotation Task 2014. | 9 |
| 14 | 15 | |
| 15 | 2 | |
| 16 | 8 | |
| 17 | 9 | |
| 18 | VAS Formalism in VASE | 1 |
| 19 | The VAS formalism in VASE | 1 |
| 20 | Specifying Input and Output of Visual Languages | 2 |
About Suzan Üsküdarlı
Suzan Üsküdarlı is a scholar working on Software, Human Factors and Ergonomics and Artificial Intelligence, having authored 33 papers that have together received 173 indexed citations. Recurring topics across this work include Topic Modeling (12 papers), Natural Language Processing Techniques (10 papers) and Biomedical Text Mining and Ontologies (5 papers). The work is most often cited by research in Software (21 citations), Artificial Intelligence (127 citations) and Health Information Management (9 citations). Suzan Üsküdarlı has collaborated with scholars based in Türkiye, United States and Netherlands. Frequent co-authors include Tunga Güngör, Burak Acar, Arzucan Özgür, Nadin Kökciyan, Jiangbo Dang, Rüştü Türkay, José F. Aldana‐Montes, María del Mar Roldán‐García, Barış Bakır and Pınar Yolum. Their work appears in journals such as PLoS ONE, Expert Systems with Applications and IEEE Journal of Biomedical and Health Informatics.
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.