Ayaka Tsuboi

488 citations
48 papers · 358 · h-index 12

Impact in

Papers in

Ayaka Tsuboi

48 papers receiving 355 citations

Peers

Ayaka Tsuboi
Comparison fields: 5 of 70
  • Endocrinology, Diabetes and Metabolism 123
  • Physiology 116
  • Nephrology 28
  • Epidemiology 116
  • Cardiology and Cardiovascular Medicine 60
Replace Giovanna Romanato with:
Giovanna Romanato Italy
Johanna Brix Austria
Jianzhong Di China
Francesco Mittempergher Italy
Zhu Junren China
Matheni Sathananthan United States
A. Gokcel Türkiye
Mikael Støckel Denmark
Yan Ren China
Kaushik Pandit India
Ayaka Tsuboi relative to Giovanna Romanato Italy Giovanna Romanato's profile →
Citations per field
00.5×3.4×
Giovanna Romanato · 1×
Citations per year

Countries citing papers authored by Ayaka Tsuboi

Since Specialization
Citations

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

Fields of papers citing papers by Ayaka Tsuboi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201727
2 201723
3 201421
4 201718
5 201516
6 201815
7 201413
8 201713
9 201513
10 201313
11 201613
12 202012
13 201511
14 201711
15 201310
16 20158
17 20158
18 20168
19 20227
20 20167

About Ayaka Tsuboi

Ayaka Tsuboi is a scholar working on Epidemiology, Endocrinology, Diabetes and Metabolism, Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine and Physiology, having authored 48 papers that have together received 358 indexed citations. Recurring topics across this work include Adipokines, Inflammation, and Metabolic Diseases (15 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (15 papers), Blood properties and coagulation (7 papers), Adipose Tissue and Metabolism (5 papers), Liver Disease Diagnosis and Treatment (5 papers), Chronic Kidney Disease and Diabetes (5 papers), Diabetes Management and Research (4 papers) and Cardiovascular Health and Disease Prevention (4 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (123 citations), Physiology (116 citations), Nephrology (28 citations), Epidemiology (116 citations) and Cardiology and Cardiovascular Medicine (60 citations). Ayaka Tsuboi has collaborated with scholars based in Japan, China and Belgium. Frequent co-authors include Tsutomu Kazumi, Keisuke Fukuo, Miki Kurata, Mika Takeuchi, Kaori Kitaoka, Mayu Watanabe, Bin Wu, Kazuhito Mita, Takashi Hayashi and Hideki Asakawa. Their work appears in journals such as BMJ Open Diabetes Research & Care, Metabolic Syndrome and Related Disorders, Journal of Atherosclerosis and Thrombosis, Scientific Reports and Chemical and Pharmaceutical Bulletin.

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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