Misha Koshelev

34 papers receiving 269 citations

Peers

Misha Koshelev
Comparison fields: 5 of 89
  • Dermatology 41
  • Cellular and Molecular Neuroscience 65
  • Molecular Biology 117
  • General Decision Sciences 3
  • Health Informatics 2
Replace Hyekyung Lee with:
Hyekyung Lee South Korea
Jenny Hong United States
Andrea Termine Italy
Ana Castelló Ponce Spain
D. J. Townsend United States
Jiarui Yang China
Matthew K. Stein United States
Rajeev S. Ramchandran United States
Yue You China
John S. Pollack United States
Misha Koshelev relative to Hyekyung Lee South Korea Hyekyung Lee's profile →
Citations per field
00.5×3.8×
Hyekyung Lee · 1×
Citations per year

Countries citing papers authored by Misha Koshelev

Since Specialization
Citations

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

Fields of papers citing papers by Misha Koshelev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Misha Koshelev, 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 Misha Koshelev Line = papers co-authored together Misha Koshelev links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010119
2 201017
3 201417
4 201317
5 202114
6 202213
7 20219
8 19977
9 19976
10 19986
11 20196
12 20205
13 20195
14 20194
15 20203
16 20113
17 20222
18 20192
19 19992
20 20172

About Misha Koshelev

Misha Koshelev is a scholar working on Dermatology, Computational Theory and Mathematics, Oncology, Epidemiology and Pathology and Forensic Medicine, having authored 41 papers that have together received 277 indexed citations. Recurring topics across this work include Numerical Methods and Algorithms (7 papers), Cutaneous Melanoma Detection and Management (3 papers), Autoimmune Bullous Skin Diseases (3 papers), Neural Networks and Applications (3 papers), Diversity and Career in Medicine (3 papers), Polynomial and algebraic computation (3 papers), Autoimmune and Inflammatory Disorders (3 papers) and Advanced materials and composites (2 papers). The work is most often cited by research in Dermatology (41 citations), Cellular and Molecular Neuroscience (65 citations), Molecular Biology (117 citations), General Decision Sciences (3 citations) and Health Informatics (2 citations). Misha Koshelev has collaborated with scholars based in United States, Ukraine and Germany. Frequent co-authors include Satyam Sarma, Roger E. Price, Xander H.T. Wehrens, Thomas A. Cooper, Teresa S. Wright, Harry Dao, Kevin P. Lee, Rohit Gupta, Anisha B. Patel and Luc Longpré. Their work appears in journals such as Journal of the American Academy of Dermatology, Clinics in Dermatology, International Journal of Intelligent Systems, International Journal of Approximate Reasoning and Human Molecular Genetics.

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