Masato Iida
Impact in
- Modeling and Simulation top 5%
- Mathematical Biology Tumor Growth
-
- Mathematical and Theoretical Epidemiology and Ecology Models
Papers in
-
- Oral microbiology and periodontitis research 7
- Co-authors
- Hirokazu NinomiyaMasayasu MimuraDanielle HilhorstI. KodamaEiji YanagidaTakahiro KarasunoYoshio KanayamaAtsushi Nishikawa
- Journals
- Journal of Human Hypertension (4 papers)Japan Journal of Industrial and Applied Mathematics (3 papers)Scientific Reports (2 papers)British Journal of Haematology (2 papers)Journal of Diabetes and its Complications (2 papers)
- Partner nations
- JapanUnited StatesFrance
In The Last Decade
Masato Iida
63 papers receiving 729 citations
Peers
Comparison fields: 5 of 111
- Modeling and Simulation 93
- Public Health, Environmental and Occupational Health 182
- Numerical Analysis 31
- Cardiology and Cardiovascular Medicine 116
- Periodontics 22
Countries citing papers authored by Masato Iida
This map shows the geographic impact of Masato Iida'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 Masato Iida with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masato Iida more than expected).
Fields of papers citing papers by Masato Iida
This network shows the impact of papers produced by Masato Iida. 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 Masato Iida. The network helps show where Masato Iida may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Masato Iida, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 3 | |
| 4 | 2023 | 4 | |
| 5 | 2020 | 1 | |
| 6 | 2017 | 9 | |
| 7 | 2016 | 1 | |
| 8 | 2016 | 21 | |
| 9 | 2015 | 10 | |
| 10 | 2014 | 6 | |
| 11 | 2012 | 15 | |
| 12 | 2009 | 46 | |
| 13 | 2009 | 9 | |
| 14 | 2008 | 16 | |
| 15 | 2007 | 16 | |
| 16 | 1991 | 3 | |
| 17 | 1991 | 1 | |
| 18 | 1990 | 12 | |
| 19 | 1989 | 7 | |
| 20 | 1985 | 1 |
About Masato Iida
Masato Iida is a scholar working on Periodontics, Modeling and Simulation, Gastroenterology, Cardiology and Cardiovascular Medicine and Applied Mathematics, having authored 68 papers that have together received 774 indexed citations. Recurring topics across this work include Cardiovascular Function and Risk Factors (9 papers), Oral microbiology and periodontitis research (7 papers), Lymphoma Diagnosis and Treatment (7 papers), Mathematical and Theoretical Epidemiology and Ecology Models (7 papers), Glycosylation and Glycoproteins Research (5 papers), Monoclonal and Polyclonal Antibodies Research (5 papers), Advanced Mathematical Modeling in Engineering (5 papers) and Multiple Myeloma Research and Treatments (4 papers). The work is most often cited by research in Modeling and Simulation (93 citations), Public Health, Environmental and Occupational Health (182 citations), Numerical Analysis (31 citations), Cardiology and Cardiovascular Medicine (116 citations) and Periodontics (22 citations). Masato Iida has collaborated with scholars based in Japan, United States and France. Frequent co-authors include Hirokazu Ninomiya, Masayasu Mimura, Danielle Hilhorst, I. Kodama, Eiji Yanagida, Takahiro Karasuno, Yoshio Kanayama, Atsushi Nishikawa, Naoyuki Taniguchi and Tetsuo Nishiura. Their work appears in journals such as Journal of Human Hypertension, Japan Journal of Industrial and Applied Mathematics, Scientific Reports, British Journal of Haematology and Journal of Diabetes and its Complications.
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.