Maksym Kholiavchenko
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence top 10%
- Pulmonary and Respiratory Medicine
- Computer Vision and Pattern Recognition top 10%
- Health Information Management top 10%
- Co-authors
- Ilyas SirazitdinovBulat IbragimovRamil KuleevYixuan YuanIvan OseledetsAndrzej CichockiTomaž VrtovecRoi Harel
- Topics
- COVID-19 diagnosis using AI (4 papers)Video Surveillance and Tracking Methods (3 papers)Radiomics and Machine Learning in Medical Imaging (2 papers)
- Journals
- International Journal of Computer VisionIEEE Journal of Biomedical and Health InformaticsMultimedia Tools and Applications
- Partner nations
- RussiaUnited StatesGermany
In The Last Decade
Maksym Kholiavchenko
8 papers receiving 282 citations
Peers
Comparison fields: 5 of 63
- Radiology, Nuclear Medicine and Imaging 214
- Artificial Intelligence 111
- Pulmonary and Respiratory Medicine 78
- Computer Vision and Pattern Recognition 60
- Health Information Management 19
Countries citing papers authored by Maksym Kholiavchenko
This map shows the geographic impact of Maksym Kholiavchenko'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 Maksym Kholiavchenko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maksym Kholiavchenko more than expected).
Fields of papers citing papers by Maksym Kholiavchenko
This network shows the impact of papers produced by Maksym Kholiavchenko. 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 Maksym Kholiavchenko. The network helps show where Maksym Kholiavchenko may publish in the future.
Co-authorship network of co-authors of Maksym Kholiavchenko
This figure shows the co-authorship network connecting the top 25 collaborators of Maksym Kholiavchenko. A scholar is included among the top collaborators of Maksym Kholiavchenko 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 Maksym Kholiavchenko. Maksym Kholiavchenko is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 5 | |
| 3 | 3 | |
| 4 | 35 | |
| 5 | 35 | |
| 6 | 35 | |
| 7 | 19 | |
| 8 | 154 |
About Maksym Kholiavchenko
Maksym Kholiavchenko is a scholar working on Computational Mathematics, General Dentistry and Radiology, Nuclear Medicine and Imaging, having authored 8 papers that have together received 290 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (4 papers), Video Surveillance and Tracking Methods (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). The work is most often cited by research in Computational Mathematics (16 citations), Health Informatics (14 citations) and Radiology, Nuclear Medicine and Imaging (214 citations). Maksym Kholiavchenko has collaborated with scholars based in Russia, United States and Germany. Frequent co-authors include Ilyas Sirazitdinov, Bulat Ibragimov, Ramil Kuleev, Yixuan Yuan, Ivan Oseledets, Andrzej Cichocki, Tomaž Vrtovec, Roi Harel, Tanya Berger‐Wolf and Daniel I. Rubenstein. Their work appears in journals such as International Journal of Computer Vision, IEEE Journal of Biomedical and Health Informatics and Multimedia Tools and Applications.
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.