Mitsuo Uchida

1.0k citations
56 papers · 708 · h-index 15

Impact in

Papers in

Mitsuo Uchida

51 papers receiving 685 citations

Peers

Mitsuo Uchida
Comparison fields: 5 of 140
  • Modeling and Simulation 62
  • Physical Therapy, Sports Therapy and Rehabilitation 54
  • Health, Toxicology and Mutagenesis 76
  • Computer Vision and Pattern Recognition 108
  • Periodontics 16
Replace Yoshitoku Yoshida with:
Yoshitoku Yoshida Japan
Mahendra Singh India
Piers R. Boshier United Kingdom
Laurent Bourguignon France
Swapnil Tiwari India
Shihua Zhu United Kingdom
Dong Eun Lee South Korea
Yu‐Shi Tian Japan
Jingya Xu China
Atul Sharma United States
Mitsuo Uchida relative to Yoshitoku Yoshida Japan Yoshitoku Yoshida's profile →
Citations per field
00.5×10×15.4×
Yoshitoku Yoshida · 1×
Citations per year

Countries citing papers authored by Mitsuo Uchida

Since Specialization
Citations

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

Fields of papers citing papers by Mitsuo Uchida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009150
2 200572
3 201533
4 201632
5 200431
6 197328
7 200726
8 201925
9 200623
10 201622
11 201119
12 199616
13 202115
14 197814
15 201214
16 200714
17 201113
18 196913
19 201112
20 200012

About Mitsuo Uchida

Mitsuo Uchida is a scholar working on Epidemiology, Modeling and Simulation, Infectious Diseases, Health, Toxicology and Mutagenesis and Organic Chemistry, having authored 56 papers that have together received 708 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (11 papers), COVID-19 epidemiological studies (9 papers), Respiratory viral infections research (6 papers), Viral Infections and Outbreaks Research (3 papers), Synthesis and Characterization of Heterocyclic Compounds (2 papers), Synthesis and Reactions of Organic Compounds (2 papers), Workplace Health and Well-being (2 papers) and Intermetallics and Advanced Alloy Properties (2 papers). The work is most often cited by research in Modeling and Simulation (62 citations), Physical Therapy, Sports Therapy and Rehabilitation (54 citations), Health, Toxicology and Mutagenesis (76 citations), Computer Vision and Pattern Recognition (108 citations) and Periodontics (16 citations). Mitsuo Uchida has collaborated with scholars based in Japan, United Kingdom and Mongolia. Frequent co-authors include T. Tamura, M. Sekine, Shigeyuki Kawa, Minoru Kaneko, V.B. Mikhailik, Minoru Itoh, H. Kraus, Hidekuni Inadera, Takayuki Honda and Minoru Kasuya. Their work appears in journals such as BMC Public Health, Chemical and Pharmaceutical Bulletin, Toxicology Letters, The Journal of Dermatology and Industrial Health.

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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