Utku Köse
Impact in
- Health Informatics top 2%
-
- Online Learning and Analytics
Papers in
-
- Machine Learning in Healthcare 8
- Metaheuristic Optimization Algorithms Research 8
- AI in cancer detection 7
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- COVID-19 diagnosis using AI 9
- Co-authors
- Ömer Deperlioğlu (22 shared papers)José Antonio Marmolejo-Saucedo (11 shared papers)Ahmet Arslan (7 shared papers)Jafar A. Alzubi (4 shared papers)Deepak Gupta (5 shared papers)Suyash Bhardwaj (2 shared papers)Gür Emre Güraksın (8 shared papers)D. Jude Hemanth (7 shared papers)
- Journals
- Wireless Networks (6 papers)IEEE Access (5 papers)Computer Applications in Engineering Education (3 papers)Applied Sciences (2 papers)International journal of engineering education (1 paper)
- Partner nations
- TürkiyeIndiaKazakhstan
In The Last Decade
Utku Köse
131 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 156
- Health Informatics 66
- Computer Science Applications 142
- Health Information Management 72
- Information Systems 299
- Artificial Intelligence 411
Countries citing papers authored by Utku Köse
This map shows the geographic impact of Utku Köse'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 Utku Köse with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Utku Köse more than expected).
Fields of papers citing papers by Utku Köse
This network shows the impact of papers produced by Utku Köse. 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 Utku Köse. The network helps show where Utku Köse may publish in the future.
Co-authors
The 25 scholars most cited alongside Utku Köse, 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 148 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 89 | |
| 2 | 2022 | 86 | |
| 3 | 2010 | 82 | |
| 4 | 2010 | 80 | |
| 5 | 2010 | 61 | |
| 6 | 2020 | 60 | |
| 7 | 2021 | 58 | |
| 8 | 2023 | 43 | |
| 9 | 2019 | 43 | |
| 10 | 2018 | 41 | |
| 11 | 2022 | 38 | |
| 12 | 2017 | 37 | |
| 13 | 2018 | 32 | |
| 14 | 2013 | 31 | |
| 15 | 2017 | 31 | |
| 16 | 2019 | 29 | |
| 17 | 2010 | 29 | |
| 18 | 2021 | 26 | |
| 19 | 2011 | 23 | |
| 20 | 2023 | 23 |
About Utku Köse
Utku Köse is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Computer Networks and Communications and Health Information Management, having authored 148 papers that have together received 1.6k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (12 papers), COVID-19 diagnosis using AI (9 papers), Machine Learning in Healthcare (8 papers), Stock Market Forecasting Methods (8 papers), Metaheuristic Optimization Algorithms Research (8 papers), AI in cancer detection (7 papers), Online Learning and Analytics (6 papers) and Experimental Learning in Engineering (6 papers). The work is most often cited by research in Health Informatics (66 citations), Computer Science Applications (142 citations), Health Information Management (72 citations), Information Systems (299 citations) and Artificial Intelligence (411 citations). Utku Köse has collaborated with scholars based in Türkiye, India and Kazakhstan. Frequent co-authors include Ömer Deperlioğlu, José Antonio Marmolejo-Saucedo, Ahmet Arslan, Jafar A. Alzubi, Deepak Gupta, Suyash Bhardwaj, Gür Emre Güraksın, D. Jude Hemanth, Ashish Khanna and Pandian Vasant. Their work appears in journals such as Wireless Networks, IEEE Access, Computer Applications in Engineering Education, Applied Sciences and International journal of engineering education.
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.