Oleg Metsker

436 total citations
40 papers, 221 citations indexed

About

Oleg Metsker is a scholar working on Epidemiology, Artificial Intelligence and Political Science and International Relations. According to data from OpenAlex, Oleg Metsker has authored 40 papers receiving a total of 221 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Epidemiology, 9 papers in Artificial Intelligence and 7 papers in Political Science and International Relations. Recurrent topics in Oleg Metsker's work include Artificial Intelligence in Law (7 papers), Digital Transformation in Law (4 papers) and Artificial Intelligence in Healthcare (4 papers). Oleg Metsker is often cited by papers focused on Artificial Intelligence in Law (7 papers), Digital Transformation in Law (4 papers) and Artificial Intelligence in Healthcare (4 papers). Oleg Metsker collaborates with scholars based in Russia, Italy and Netherlands. Oleg Metsker's co-authors include Sergey V. Kovalchuk, A. N. Yakovlev, Georgy Kopanitsa, Н. Э. Звартау, Valeria V. Krzhizhanovskaya, Е. V. Shlyakhto, Giuseppe Faggian, Anna Kostareva, O. B. Irtyuga and Anna Malashicheva and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American College of Cardiology and Journal of the Neurological Sciences.

In The Last Decade

Oleg Metsker

30 papers receiving 205 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Oleg Metsker Russia 8 92 56 33 30 25 40 221
Margrét V. Bjarnadóttir United States 8 95 1.0× 51 0.9× 12 0.4× 43 1.4× 27 1.1× 37 344
Bakheet Aldosari Saudi Arabia 11 52 0.6× 174 3.1× 32 1.0× 25 0.8× 46 1.8× 38 366
Fatemeh Navidi Iran 3 71 0.8× 128 2.3× 60 1.8× 17 0.6× 25 1.0× 8 295
Teresa Zayas‐Cabán United States 11 33 0.4× 127 2.3× 9 0.3× 19 0.6× 16 0.6× 29 335
Grahame Grieve United States 7 83 0.9× 105 1.9× 18 0.5× 9 0.3× 47 1.9× 9 272
Eliot Kimber United Kingdom 3 115 1.3× 138 2.5× 22 0.7× 13 0.4× 27 1.1× 8 352
Linas Simonaitis United States 10 63 0.7× 278 5.0× 8 0.2× 26 0.9× 44 1.8× 19 436
Yesha Raval United States 3 62 0.7× 81 1.4× 32 1.0× 28 0.9× 28 1.1× 4 248
Itamar Shabtai Israel 9 52 0.6× 194 3.5× 14 0.4× 21 0.7× 50 2.0× 22 366
Fernando Rua Portugal 8 63 0.7× 72 1.3× 19 0.6× 23 0.8× 17 0.7× 38 190

Countries citing papers authored by Oleg Metsker

Since Specialization
Citations

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

Fields of papers citing papers by Oleg Metsker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Oleg Metsker. 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 Oleg Metsker. The network helps show where Oleg Metsker may publish in the future.

Co-authorship network of co-authors of Oleg Metsker

This figure shows the co-authorship network connecting the top 25 collaborators of Oleg Metsker. A scholar is included among the top collaborators of Oleg Metsker 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 Oleg Metsker. Oleg Metsker is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kopanitsa, Georgy & Oleg Metsker. (2024). Unraveling Endometrial Cancer Survival Predictors Through Advanced Machine Learning Techniques. Studies in health technology and informatics. 314. 127–131.
2.
Kopanitsa, Georgy, Oleg Metsker, & Sergey V. Kovalchuk. (2023). Machine Learning Methods for Pregnancy and Childbirth Risk Management. Journal of Personalized Medicine. 13(6). 975–975. 8 indexed citations
3.
Irtyuga, O. B., Anna Kostareva, Giuseppe Faggian, et al.. (2023). Analysis of Prevalence and Clinical Features of Aortic Stenosis in Patients with and without Bicuspid Aortic Valve Using Machine Learning Methods. Journal of Personalized Medicine. 13(11). 1588–1588. 4 indexed citations
4.
Irtyuga, O. B., Georgy Kopanitsa, Anna Kostareva, et al.. (2022). Application of Machine Learning Methods to Analyze Occurrence and Clinical Features of Ascending Aortic Dilatation in Patients with and without Bicuspid Aortic Valve. Journal of Personalized Medicine. 12(5). 794–794. 4 indexed citations
5.
Metsker, Oleg, et al.. (2021). Regulation Modelling and Analysis Using Machine Learning During the Covid-19 Pandemic in Russia. Studies in health technology and informatics. 285. 259–264. 1 indexed citations
6.
Metsker, Oleg, et al.. (2021). Application of Machine Learning for E-justice. Journal of Physics Conference Series. 1828(1). 12006–12006. 2 indexed citations
7.
Metsker, Oleg, et al.. (2020). Prediction of Childbirth Mortality Using Machine Learning. Studies in health technology and informatics. 273. 109–114. 3 indexed citations
8.
Metsker, Oleg, et al.. (2020). Prediction of a Due Date Based on the Pregnancy History Data Using Machine Learning. Studies in health technology and informatics. 273. 104–108. 5 indexed citations
9.
Metsker, Oleg, et al.. (2020). Identification of Diabetes Risk Factors in Chronic Cardiovascular Patients. Studies in health technology and informatics. 273. 136–141. 7 indexed citations
10.
Metsker, Oleg, et al.. (2020). Identification of risk factors for patients with diabetes: diabetic polyneuropathy case study. BMC Medical Informatics and Decision Making. 20(1). 201–201. 19 indexed citations
11.
12.
Metsker, Oleg, et al.. (2019). Risk markers identification in EHR using natural language processing: hemorrhagic and ischemic stroke cases. Procedia Computer Science. 156. 142–149. 5 indexed citations
13.
14.
Metsker, Oleg, et al.. (2019). Sepsis prediction using machine-learning methods: prolonged disorders of consciousness patients. Journal of the Neurological Sciences. 405. 83–83. 1 indexed citations
15.
Kovalchuk, Sergey V., et al.. (2018). Simulation of patient flow in multiple healthcare units using process and data mining techniques for model identification. Journal of Biomedical Informatics. 82. 128–142. 60 indexed citations
16.
Yakovlev, A. N., et al.. (2018). PREDICTION OF IN-HOSPITAL MORTALITY AND LENGTH OF STAY IN ACUTE CORONARY SYNDROME PATIENTS USING MACHINE-LEARNING METHODS. Journal of the American College of Cardiology. 71(11). A242–A242. 17 indexed citations
17.
Kovalchuk, Sergey V., et al.. (2018). Towards management of complex modeling through a hybrid evolutionary identification. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 255–256.
18.
Metsker, Oleg, et al.. (2018). Dynamic mortality prediction using machine learning techniques for acute cardiovascular cases. Procedia Computer Science. 136. 351–358. 10 indexed citations
19.
Metsker, Oleg, et al.. (2018). Investigating Application of Change Point Analysis in Monitoring Health Condition of Acute Coronary Syndrome Patients. Procedia Computer Science. 136. 408–415. 1 indexed citations
20.
Metsker, Oleg, et al.. (2018). Identification of Pathophysiological Subclinical Variances During Complex Treatment Process of Cardiovascular Patients. Procedia Computer Science. 138. 161–168. 3 indexed citations

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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2026