Fuki Ikeda

1.5k citations
39 papers · 778 · h-index 15

Impact in

Papers in

Fuki Ikeda

35 papers receiving 761 citations

Peers

Fuki Ikeda
Comparison fields: 5 of 72
  • Endocrinology, Diabetes and Metabolism 207
  • Cardiology and Cardiovascular Medicine 178
  • Physiology 102
  • Surgery 167
  • Nephrology 23
Replace Adam Sheka with:
Adam Sheka United States
Jiaqing Shao China
Hassan Azhari Canada
Masaaki Eto Japan
Xin Su China
Hongdong Wang China
Shigehiro Karashima Japan
L.D. Dikkeschei Netherlands
Yanzhen Cheng China
Emanuela Laratta Italy
Fuki Ikeda relative to Adam Sheka United States Adam Sheka's profile →
Citations per field
00.5×4.3×
Adam Sheka · 1×
Citations per year

Countries citing papers authored by Fuki Ikeda

Since Specialization
Citations

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

Fields of papers citing papers by Fuki Ikeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017112
2 200678
3 200865
4 200362
5 201161
6 200340
7 201740
8 201136
9 201131
10 200930
11 200628
12 201719
13 200817
14 201516
15 200815
16 202014
17 201914
18 201811
19 201211
20 20159

About Fuki Ikeda

Fuki Ikeda is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery, Cardiology and Cardiovascular Medicine, Molecular Biology and Genetics, having authored 39 papers that have together received 778 indexed citations. Recurring topics across this work include Diabetes Treatment and Management (7 papers), Pancreatic function and diabetes (6 papers), Diabetes Management and Research (5 papers), Diabetes and associated disorders (3 papers), Liver physiology and pathology (2 papers), Blood Pressure and Hypertension Studies (2 papers), Cardiovascular Function and Risk Factors (2 papers) and Cardiac Imaging and Diagnostics (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (207 citations), Cardiology and Cardiovascular Medicine (178 citations), Physiology (102 citations), Surgery (167 citations) and Nephrology (23 citations). Fuki Ikeda has collaborated with scholars based in Japan and United States. Frequent co-authors include Hirotaka Watada, Ryuzo Kawamori, Tomoaki Shimizu, Akio Kanazawa, Takahisa Hirose, Tomoya Mita, Takeshi Ogihara, Yoshio Fujitani, Kosuke Azuma and Koji Komiya. Their work appears in journals such as Journal of Diabetes Investigation, Diabetologia, Biochemical and Biophysical Research Communications, Circulation Journal and Diabetes Care.

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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