Evgenii E. Vityaev

795 citations
70 papers · 487 · h-index 11

Impact in

Papers in

Evgenii E. Vityaev

63 papers receiving 448 citations

Peers

Evgenii E. Vityaev
Comparison fields: 5 of 91
  • Artificial Intelligence 245
  • Aging 11
  • Computational Theory and Mathematics 94
  • Health Information Management 21
  • Information Systems 75
Replace Teresa Mroczek with:
Teresa Mroczek Poland
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Sherine Rady Egypt
Renqian Luo China
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Citations per year

Countries citing papers authored by Evgenii E. Vityaev

Since Specialization
Citations

This map shows the geographic impact of Evgenii E. Vityaev'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 Evgenii E. Vityaev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Evgenii E. Vityaev more than expected).

Fields of papers citing papers by Evgenii E. Vityaev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Evgenii E. Vityaev. 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 Evgenii E. Vityaev. The network helps show where Evgenii E. Vityaev may publish in the future.

Co-authors

The 20 scholars most cited alongside Evgenii E. Vityaev, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Evgenii E. Vityaev Line = papers co-authored together Evgenii E. Vityaev links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200442
2
Data Mining in Finance: Advances in Relational and Hybrid Methods
201336
3 200036
4 199634
5
Consistent and complete data and “expert” mining in medicine
200329
6 200623
7 201220
8 200016
9 200415
10 200912
11 201312
12 201511
13 20159
14 20088
15 20138
16 20068
17 20088
18 20127
19 20117
20 20186

About Evgenii E. Vityaev

Evgenii E. Vityaev is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Information Systems, Management Science and Operations Research and Molecular Biology, having authored 70 papers that have together received 487 indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (14 papers), Semantic Web and Ontologies (12 papers), Data Mining Algorithms and Applications (12 papers), Cognitive Science and Mapping (11 papers), RNA and protein synthesis mechanisms (8 papers), Biomedical Text Mining and Ontologies (5 papers), Neural Networks and Applications (5 papers) and Bayesian Modeling and Causal Inference (5 papers). The work is most often cited by research in Artificial Intelligence (245 citations), Aging (11 citations), Computational Theory and Mathematics (94 citations), Health Information Management (21 citations) and Information Systems (75 citations). Evgenii E. Vityaev has collaborated with scholars based in Russia, United States and Italy. Frequent co-authors include Boris Kovalerchuk, Alexander V. Demin, Evangelos Triantaphyllou, Elena V. Ignatieva, Dmitry Y. Oshchepkov, Tamara M. Khlebodarova, Nikolay Alexandrovich Kolchanov, Yuriy Lvovich Orlov, Vetle I. Torvik and LEONID I. PERLOVSKY. Their work appears in journals such as Cognitive Systems Research, Vision Research, Information Sciences, Minds and Machines and Nucleic Acids Research.

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.

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