Roman Tkachenko
Impact in
-
- Artificial Intelligence in Healthcare
-
- Information Systems and Technology Applications
Papers in
-
- Statistical and Computational Modeling 11
- Neural Networks and Applications 5
- Machine Learning and Data Classification 4
-
- Information Systems and Technology Applications 18
- Co-authors
- Ivan Izonin (52 shared papers)Khrystyna Zub (9 shared papers)Nataliia Lotoshynska (6 shared papers)Natalia Kryvinska (7 shared papers)Ivanna Dronyuk (5 shared papers)Nataliya Shakhovska (5 shared papers)Zoia Duriagina (10 shared papers)Michal Greguš (7 shared papers)
In The Last Decade
Roman Tkachenko
60 papers receiving 791 citations
Peers
Comparison fields: 5 of 135
- Health Information Management 60
- Management Information Systems 113
- Artificial Intelligence 281
- Industrial and Manufacturing Engineering 60
- Control and Systems Engineering 110
Countries citing papers authored by Roman Tkachenko
This map shows the geographic impact of Roman Tkachenko'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 Roman Tkachenko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roman Tkachenko more than expected).
Fields of papers citing papers by Roman Tkachenko
This network shows the impact of papers produced by Roman Tkachenko. 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 Roman Tkachenko. The network helps show where Roman Tkachenko may publish in the future.
Co-authors
The 25 scholars most cited alongside Roman Tkachenko, 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 68 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 61 | |
| 2 | 2022 | 58 | |
| 3 | 2018 | 52 | |
| 4 | 2020 | 50 | |
| 5 | 2018 | 44 | |
| 6 | 2021 | 42 | |
| 7 | 2023 | 41 | |
| 8 | 2021 | 36 | |
| 9 | 2015 | 26 | |
| 10 | 2021 | 25 | |
| 11 | 2019 | 24 | |
| 12 | 2020 | 20 | |
| 13 | 2018 | 20 | |
| 14 | 2018 | 18 | |
| 15 | 2020 | 17 | |
| 16 | 2018 | 17 | |
| 17 | 2018 | 17 | |
| 18 | 2019 | 17 | |
| 19 | 2018 | 16 | |
| 20 | 2023 | 13 |
About Roman Tkachenko
Roman Tkachenko is a scholar working on Artificial Intelligence, Management Information Systems, Control and Systems Engineering, Information Systems and Industrial and Manufacturing Engineering, having authored 68 papers that have together received 856 indexed citations. Recurring topics across this work include Information Systems and Technology Applications (18 papers), Advanced Data Processing Techniques (14 papers), Advanced Computational Techniques in Science and Engineering (13 papers), Statistical and Computational Modeling (11 papers), Engineering Technology and Methodologies (10 papers), Advanced Scientific Research Methods (6 papers), Neural Networks and Applications (5 papers) and Machine Learning and Data Classification (4 papers). The work is most often cited by research in Health Information Management (60 citations), Management Information Systems (113 citations), Artificial Intelligence (281 citations), Industrial and Manufacturing Engineering (60 citations) and Control and Systems Engineering (110 citations). Roman Tkachenko has collaborated with scholars based in Ukraine, Slovakia and Austria. Frequent co-authors include Ivan Izonin, Khrystyna Zub, Nataliia Lotoshynska, Natalia Kryvinska, Ivanna Dronyuk, Nataliya Shakhovska, Zoia Duriagina, Michal Greguš, Krishna Kant Singh and Mahesh Thyluru Ramakrishna. Their work appears in journals such as Scientific Reports, Applied Sciences, Mathematical Biosciences & Engineering, Sensors and Symmetry.
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.