Seiichi Ikeda

732 citations
61 papers · 540 · h-index 15

Impact in

    • Soft Robotics and Applications
    • 3D Printing in Biomedical Research
    • Anatomy and Medical Technology
    • Electrospun Nanofibers in Biomedical Applications

Papers in

Seiichi Ikeda

58 papers receiving 509 citations

Peers

Seiichi Ikeda
Comparison fields: 5 of 76
  • Biomedical Engineering 313
  • Biomaterials 87
  • Neurology 81
  • Surgery 220
  • Condensed Matter Physics 54
Replace Jun Okamoto with:
Jun Okamoto Japan
Mohamed E. M. K. Abdelaziz United Kingdom
Sang‐Eun Song United States
Christophe Chautems Switzerland
Henry W. Haslach United States
Ang Chen China
Borhan Beigzadeh Iran
Zurab Machaidze United States
Karl Price United States
Simon Chatelin France
Seiichi Ikeda relative to Jun Okamoto Japan Jun Okamoto's profile →
Citations per field
00.5×7.7×
Jun Okamoto · 1×
Citations per year

Countries citing papers authored by Seiichi Ikeda

Since Specialization
Citations

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

Fields of papers citing papers by Seiichi Ikeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200548
2 200743
3 200941
4 201234
5 201323
6 201223
7 200521
8 201321
9 201221
10 201018
11 201617
12 200715
13 201315
14 201014
15 199614
16 199414
17 200613
18 200910
19 19759
20 20119

About Seiichi Ikeda

Seiichi Ikeda is a scholar working on Biomedical Engineering, Pulmonary and Respiratory Medicine, Surgery, Neurology and Biomaterials, having authored 61 papers that have together received 540 indexed citations. Recurring topics across this work include Cerebrovascular and Carotid Artery Diseases (20 papers), Intracranial Aneurysms: Treatment and Complications (18 papers), Electrospun Nanofibers in Biomedical Applications (12 papers), Tissue Engineering and Regenerative Medicine (9 papers), Surgical Simulation and Training (9 papers), 3D Printing in Biomedical Research (8 papers), Anatomy and Medical Technology (7 papers) and Cardiovascular Health and Disease Prevention (6 papers). The work is most often cited by research in Biomedical Engineering (313 citations), Biomaterials (87 citations), Neurology (81 citations), Surgery (220 citations) and Condensed Matter Physics (54 citations). Seiichi Ikeda has collaborated with scholars based in Japan, Australia and China. Frequent co-authors include Toshio Fukuda, Fumihito Arai, Makoto Negoro, Keiko Irie, Bijan Shirinzadeh, Ikuo Takahashi, Adriano Cavalcanti, Chaoyang Shi, Tomoyuki Uchida and Takehisa Matsuda. Their work appears in journals such as Journal of the Japan Institute of Metals and Materials, Japanese Journal of Applied Physics, Journal of Biotechnology, Biomicrofluidics and Advanced Robotics.

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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