Keisuke Ejima
Impact in
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies
- Aging top 5%
- Genetics, Aging, and Longevity in Model Organisms
Papers in
-
- SARS-CoV-2 and COVID-19 Research 11
- SARS-CoV-2 detection and testing 8
- COVID-19 Clinical Research Studies 4
- Epidemiology 19
- Traumatic Brain Injury Research 9
- Influenza Virus Research Studies 4
- Co-authors
- Hiroshi Nishiura (21 shared papers)Kazuyuki Aihara (14 shared papers)Shingo Iwami (18 shared papers)David B. Allison (19 shared papers)Keisuke Kawata (11 shared papers)Kenji Mizumoto (5 shared papers)Shoya Iwanami (10 shared papers)Kwang Su Kim (9 shared papers)
- Journals
- Theoretical Biology and Medical Modelling (4 papers)Journal of Theoretical Biology (4 papers)Obesity (3 papers)PLoS ONE (3 papers)The Lancet Regional Health - Western Pacific (2 papers)
- Partner nations
- United StatesJapanSingapore
In The Last Decade
Keisuke Ejima
76 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 121
- Modeling and Simulation 231
- Aging 63
- Infectious Diseases 272
- Epidemiology 288
- Virology 34
Countries citing papers authored by Keisuke Ejima
This map shows the geographic impact of Keisuke Ejima'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 Keisuke Ejima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keisuke Ejima more than expected).
Fields of papers citing papers by Keisuke Ejima
This network shows the impact of papers produced by Keisuke Ejima. 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 Keisuke Ejima. The network helps show where Keisuke Ejima may publish in the future.
Co-authors
The 25 scholars most cited alongside Keisuke Ejima, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 124 | |
| 2 | 2021 | 91 | |
| 3 | 2021 | 42 | |
| 4 | 2021 | 34 | |
| 5 | 2020 | 34 | |
| 6 | 2020 | 33 | |
| 7 | 2020 | 33 | |
| 8 | 2019 | 32 | |
| 9 | 2021 | 32 | |
| 10 | 2018 | 32 | |
| 11 | 2020 | 30 | |
| 12 | 2014 | 30 | |
| 13 | 2013 | 29 | |
| 14 | 2016 | 24 | |
| 15 | 2012 | 24 | |
| 16 | 2013 | 23 | |
| 17 | 2012 | 22 | |
| 18 | 2018 | 22 | |
| 19 | 2022 | 21 | |
| 20 | 2012 | 21 |
About Keisuke Ejima
Keisuke Ejima is a scholar working on Infectious Diseases, Epidemiology, Modeling and Simulation, Virology and Public Health, Environmental and Occupational Health, having authored 81 papers that have together received 1.1k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (15 papers), SARS-CoV-2 and COVID-19 Research (11 papers), Traumatic Brain Injury Research (9 papers), SARS-CoV-2 detection and testing (8 papers), HIV Research and Treatment (6 papers), COVID-19 Clinical Research Studies (4 papers), Genetics, Aging, and Longevity in Model Organisms (4 papers) and Influenza Virus Research Studies (4 papers). The work is most often cited by research in Modeling and Simulation (231 citations), Aging (63 citations), Infectious Diseases (272 citations), Epidemiology (288 citations) and Virology (34 citations). Keisuke Ejima has collaborated with scholars based in United States, Japan and Singapore. Frequent co-authors include Hiroshi Nishiura, Kazuyuki Aihara, Shingo Iwami, David B. Allison, Keisuke Kawata, Kenji Mizumoto, Shoya Iwanami, Kwang Su Kim, Yasuhisa Fujita and Megan E. Huibregtse. Their work appears in journals such as Theoretical Biology and Medical Modelling, Journal of Theoretical Biology, Obesity, PLoS ONE and The Lancet Regional Health - Western Pacific.
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.