Martynov Ai

842 total citations
57 papers, 109 citations indexed

About

Martynov Ai is a scholar working on Cardiology and Cardiovascular Medicine, Epidemiology and Neurology. According to data from OpenAlex, Martynov Ai has authored 57 papers receiving a total of 109 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Cardiology and Cardiovascular Medicine, 13 papers in Epidemiology and 8 papers in Neurology. Recurrent topics in Martynov Ai's work include Healthcare Systems and Public Health (11 papers), Neurological Disorders and Treatments (8 papers) and Lipoproteins and Cardiovascular Health (4 papers). Martynov Ai is often cited by papers focused on Healthcare Systems and Public Health (11 papers), Neurological Disorders and Treatments (8 papers) and Lipoproteins and Cardiovascular Health (4 papers). Martynov Ai collaborates with scholars based in Russia, United States and Czechia. Martynov Ai's co-authors include Е. В. Акатова, Yury P. Zinchenko, I. Yu. Torshin, О. А. Громова, О. Д. Остроумова, Н. В. Чичасова, А. И. Чесникова, В. В. Фомин, Mazurov Vi and Е. В. Ощепкова and has published in prestigious journals such as SHILAP Revista de lepidopterología, European Psychiatry and Cardiology.

In The Last Decade

Martynov Ai

47 papers receiving 92 citations

Peers

Martynov Ai
Comparison fields: 5 of 64
  • Cardiology and Cardiovascular Medicine 29
  • Epidemiology 22
  • Rheumatology 13
  • Molecular Biology 11
  • Pediatrics, Perinatology and Child Health 11
Replace И Е Чазова with:
И Е Чазова Russia
Amanda Chang United States
О. Аbrahamovych Ukraine
Jing Hong China
Sulaiman Sultan United States
Nicole Kosik United States
Christelle Cantet France
E. Oschepkova Russia
Jelena Stanarčić Gajović Serbia
И Е Чазова Russia View profile →
Citations per field, relative to Martynov Ai
Martynov Ai · 1×
Citations per year, relative to Martynov Ai
Martynov Ai · 1×

Countries citing papers authored by Martynov Ai

Since Specialization
Citations

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

Fields of papers citing papers by Martynov Ai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martynov Ai

This figure shows the co-authorship network connecting the top 25 collaborators of Martynov Ai. A scholar is included among the top collaborators of Martynov Ai 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 Martynov Ai. Martynov Ai 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
# Work Indexed citations
1 3
2 5
3 2
4 1
5 0
6 1
7 0
8 1
9 5
10 12
11 3
12 1
13 1
14 1
15
Поведенческий тип а и острый коронарный синдром
1
16 1
17 1
18
Hyperhomocysteinemia and acute phase proteins in various forms of ischemic heart disease
1
19
Diroton effects on 24-h fluctuations of arterial pressure as shown bymonitoring in hypertensive patients with polycythemia vera
1
20 2

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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