Mikhail Belyaev

15 papers receiving 356 citations

Peers

Mikhail Belyaev
Comparison fields: 5 of 69
  • Neurology 169
  • Health Informatics 17
  • Health Information Management 27
  • Psychiatry and Mental health 82
  • Artificial Intelligence 146
Replace L. Khedher with:
L. Khedher Spain
A. Brahim Spain
Yulia Dodonova Russia
Sergey Korolev Russia
Kanghan Oh South Korea
Elina Thibeau–Sutre France
Akshay Pai Denmark
Dan Pan China
Siqi Liu China
Ahmad Al Smadi China
Mikhail Belyaev relative to L. Khedher Spain L. Khedher's profile →
Citations per field
00.5×1.5×1.8×
L. Khedher · 1×
Citations per year

Countries citing papers authored by Mikhail Belyaev

Since Specialization
Citations

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

Fields of papers citing papers by Mikhail Belyaev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Mikhail Belyaev, 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 Mikhail Belyaev Line = papers co-authored together Mikhail Belyaev links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2017273
2 202218
3 201412
4 201611
5 201611
6 202111
7 20225
8 20233
9 20163
10 20143
11 20163
12 20153
13 20162
14 20231
15 20201
16 20240
17 20250
18 20190

About Mikhail Belyaev

Mikhail Belyaev is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, Biomedical Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 18 papers that have together received 360 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), Neural dynamics and brain function (3 papers), Artificial Intelligence in Healthcare and Education (2 papers), Brain Tumor Detection and Classification (2 papers), Advanced X-ray and CT Imaging (2 papers), Medical Image Segmentation Techniques (2 papers), Advanced Neural Network Applications (2 papers) and Medical Imaging and Analysis (2 papers). The work is most often cited by research in Neurology (169 citations), Health Informatics (17 citations), Health Information Management (27 citations), Psychiatry and Mental health (82 citations) and Artificial Intelligence (146 citations). Mikhail Belyaev has collaborated with scholars based in Russia, United States and Tajikistan. Frequent co-authors include Yulia Dodonova, Sergey Korolev, Evgeny Burnaev, Victor А. Gombolevskiy, С. П. Морозов, Alexey Zakharov, Andrey Golanov, Pavel Prikhodko, Mikhail Galkin and Leonid Zhukov. Their work appears in journals such as Asian Spine Journal, IEEE Journal of Biomedical and Health Informatics, Medical Image Analysis, Journal of Neurology Neurosurgery & Psychiatry and Advanced materials 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.

Explore authors with similar magnitude of impact