Koichiro Kadota
- Cardiology and Cardiovascular Medicine top 5%
- Physiology top 10%
- Epidemiology
- Endocrinology, Diabetes and Metabolism top 10%
- Immunology
- Co-authors
- Takahiro MaedaYūji ShimizuNoboru TakamuraMako NagayoshiMio NakazatoJun KoyamatsuHironori YamasakiKiyoshi Aoyagi
- Topics
- Adipokines, Inflammation, and Metabolic Diseases (14 papers)Cardiovascular Health and Disease Prevention (10 papers)Inflammatory Biomarkers in Disease Prognosis (8 papers)
- Cited by
- Cardiology and Cardiovascular MedicineEndocrinology, Diabetes and MetabolismGeriatrics and Gerontology
- Journals
- AtherosclerosisOncotargetBMJ Open
- Partner nations
- JapanAustraliaUnited States
In The Last Decade
Koichiro Kadota
48 papers receiving 849 citations
Peers
Comparison fields: 5 of 81
- Cardiology and Cardiovascular Medicine 383
- Physiology 190
- Epidemiology 187
- Endocrinology, Diabetes and Metabolism 187
- Immunology 115
Countries citing papers authored by Koichiro Kadota
This map shows the geographic impact of Koichiro Kadota'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 Koichiro Kadota with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Koichiro Kadota more than expected).
Fields of papers citing papers by Koichiro Kadota
This network shows the impact of papers produced by Koichiro Kadota. 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 Koichiro Kadota. The network helps show where Koichiro Kadota may publish in the future.
Co-authorship network of co-authors of Koichiro Kadota
This figure shows the co-authorship network connecting the top 25 collaborators of Koichiro Kadota. A scholar is included among the top collaborators of Koichiro Kadota based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Koichiro Kadota. Koichiro Kadota is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 18 | |
| 3 | 38 | |
| 4 | 21 | |
| 5 | 24 | |
| 6 | 14 | |
| 7 | 15 | |
| 8 | 14 | |
| 9 | 21 | |
| 10 | 9 | |
| 11 | 4 | |
| 12 | 6 | |
| 13 | 8 | |
| 14 | 8 | |
| 15 | 61 | |
| 16 | 24 | |
| 17 | 15 | |
| 18 | 14 | |
| 19 | 13 | |
| 20 | 1 |
About Koichiro Kadota
Koichiro Kadota is a scholar working on Endocrinology, Diabetes and Metabolism, Cardiology and Cardiovascular Medicine and Nephrology, having authored 50 papers that have together received 869 indexed citations. Recurring topics across this work include Adipokines, Inflammation, and Metabolic Diseases (14 papers), Cardiovascular Health and Disease Prevention (10 papers) and Inflammatory Biomarkers in Disease Prognosis (8 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (383 citations), Endocrinology, Diabetes and Metabolism (187 citations) and Geriatrics and Gerontology (40 citations). Koichiro Kadota has collaborated with scholars based in Japan, Australia and United States. Frequent co-authors include Takahiro Maeda, Yūji Shimizu, Noboru Takamura, Mako Nagayoshi, Mio Nakazato, Jun Koyamatsu, Hironori Yamasaki, Kiyoshi Aoyagi, Hirotomo Yamanashi and Shimpei Sato. Their work appears in journals such as Atherosclerosis, Oncotarget and BMJ Open.
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.