Ryo Ito

87 papers receiving 1.7k citations

Peers

Ryo Ito
Comparison fields: 5 of 147
  • Endocrinology, Diabetes and Metabolism 384
  • Developmental Biology 40
  • Computer Vision and Pattern Recognition 247
  • Surgery 397
  • Molecular Biology 542
Replace Michael J. Black with:
Michael J. Black United States
Matthew J. Callow United States
Wen Chen China
Jian Qiu China
Mika Sato Japan
D. Srinivasa Rao India
Jianshuang Li China
Sung Hak Lee South Korea
Ming Wang China
Yiliang Chen United States
Ryo Ito relative to Michael J. Black United States Michael J. Black's profile →
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Citations per year

Countries citing papers authored by Ryo Ito

Since Specialization
Citations

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

Fields of papers citing papers by Ryo Ito

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 94 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010217
2
Image Size Invariant Visual Cryptography
1999213
3 2011130
4 2015115
5 201381
6 201269
7 201364
8 201961
9 200954
10 201445
11 198642
12 201140
13 201338
14 201334
15 201930
16 201727
17 202026
18 201225
19 202225
20 201924

About Ryo Ito

Ryo Ito is a scholar working on Surgery, Molecular Biology, Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine and Endocrinology, Diabetes and Metabolism, having authored 94 papers that have together received 1.8k indexed citations. Recurring topics across this work include Pancreatic function and diabetes (19 papers), Cardiac pacing and defibrillation studies (8 papers), Diabetes Treatment and Management (8 papers), Cardiac Arrhythmias and Treatments (7 papers), Pluripotent Stem Cells Research (7 papers), Atrial Fibrillation Management and Outcomes (5 papers), Asymmetric Hydrogenation and Catalysis (4 papers) and Non-Destructive Testing Techniques (4 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (384 citations), Developmental Biology (40 citations), Computer Vision and Pattern Recognition (247 citations), Surgery (397 citations) and Molecular Biology (542 citations). Ryo Ito has collaborated with scholars based in Japan, United States and Madagascar. Frequent co-authors include Hatsukazu Tanaka, Hidenori Kuwakado, Yoshiyuki Tsujihata, Koji Takeuchi, Akira Mori, Nobuyuki Negoro, Masami Suzuki, Yū Momose, Tsuneo Yasuma and Ayako Harada. Their work appears in journals such as Scientific Reports, Journal of Cardiology, Journal of Pharmacology and Experimental Therapeutics, Journal of Interventional Cardiac Electrophysiology and Proceedings of the National Academy of Sciences.

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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