Satoshi Mimura

1.1k citations
19 papers · 630 · h-index 8

Impact in

Papers in

Satoshi Mimura

18 papers receiving 617 citations

Peers

Satoshi Mimura
Comparison fields: 5 of 80
  • Infectious Diseases 419
  • General Dentistry 35
  • Modeling and Simulation 55
  • Biomedical Engineering 215
  • Neurology 67
Replace Kazuyasu Miyoshi with:
Kazuyasu Miyoshi Japan
Sakiko Tabata Japan
Nam‐Joo Lee South Korea
Niko Kohmer Germany
Byron Freire‐Paspuel Ecuador
Yanhong Sun China
Timmy Wing‐Kuk Au China
Derek L.L. Hung Hong Kong
Eamon O’Murchu Ireland
Frank Tolksdorf Germany
Satoshi Mimura relative to Kazuyasu Miyoshi Japan Kazuyasu Miyoshi's profile →
Citations per field
00.5×
Kazuyasu Miyoshi · 1×
Citations per year

Countries citing papers authored by Satoshi Mimura

Since Specialization
Citations

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

Fields of papers citing papers by Satoshi Mimura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1 2020283
2 2020170
3 200270
4 201427
5 202011
6 201510
7 199910
8 20208
9 20057
10 20156
11 20145
12
Preventive Effect Against Influenza-Like Illness by Low-Concentration Chlorine Dioxide Gas
20104
13 20054
14
[Infectious disease surveillance in Miyagi after the Great East Japan Earthquake].
20134
15
[Pulmonary involvement in sarcoidosis: CT findings at diagnosis and their changes at follow-up in cases without corticosteroid treatment].
20024
16 20123
17 20192
18
[Summer-type hypersensitivity pneumonitis in monozygotic twins].
20032
19 20180

About Satoshi Mimura

Satoshi Mimura is a scholar working on Epidemiology, Infectious Diseases, Pulmonary and Respiratory Medicine, Modeling and Simulation and Biomedical Engineering, having authored 19 papers that have together received 630 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (3 papers), COVID-19 epidemiological studies (3 papers), Respiratory viral infections research (3 papers), Long-Term Effects of COVID-19 (2 papers), Fungal and yeast genetics research (2 papers), Disaster Response and Management (2 papers), Travel-related health issues (2 papers) and COVID-19 Clinical Research Studies (2 papers). The work is most often cited by research in Infectious Diseases (419 citations), General Dentistry (35 citations), Modeling and Simulation (55 citations), Biomedical Engineering (215 citations) and Neurology (67 citations). Satoshi Mimura has collaborated with scholars based in Japan, Netherlands and China. Frequent co-authors include Kaku Tamura, Toshimitsu Ito, Kazuo Imai, Sakiko Tabata, Kazuyasu Miyoshi, Yoshitaka Imoto, Yasuyuki Kato, Maki Iwata, Yasuhide Uwabe and Tatsuya Kodama. Their work appears in journals such as PLoS ONE, Microbiological Research, Journal of Clinical Microbiology, The Lancet Infectious Diseases and Fungal Genetics and Biology.

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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