Dai Kishida

1.4k citations
74 papers · 707 · h-index 15

Impact in

    • Eosinophilic Disorders and Syndromes
  • Hematology top 10%
    • Autoimmune and Inflammatory Disorders Research

Papers in

    • IgG4-Related and Inflammatory Diseases 9
    • Systemic Lupus Erythematosus Research 8
    • Inflammasome and immune disorders 21

Dai Kishida

63 papers receiving 694 citations

Peers

Dai Kishida
Comparison fields: 5 of 67
  • Rheumatology 251
  • Hematology 144
  • Immunology 240
  • Nephrology 58
  • Molecular Biology 313
Replace Qiongyi Hu with:
Qiongyi Hu China
Linda Wagner‐Weiner United States
Éric Rich Canada
R Brik Israel
Graciela Espada Argentina
Valentina Leone United Kingdom
Javier Merayo‐Chalico Mexico
M H Cardiel Mexico
Christopher C. Striebich United States
Tuyet‐Hang Pham United States
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Citations per field
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Qiongyi Hu · 1×
Citations per year

Countries citing papers authored by Dai Kishida

Since Specialization
Citations

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

Fields of papers citing papers by Dai Kishida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 74 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201471
2 201466
3 201050
4 201735
5 201128
6 201726
7 201724
8 202022
9 201321
10 201620
11 201919
12 202117
13 201015
14 201615
15 201914
16 201114
17 201711
18 202210
19
Triggering factors for febrile attacks in Japanese patients with familial Mediterranean fever.
202010
20 20239

About Dai Kishida

Dai Kishida is a scholar working on Rheumatology, Molecular Biology, Immunology, Pulmonary and Respiratory Medicine and Surgery, having authored 74 papers that have together received 707 indexed citations. Recurring topics across this work include Inflammasome and immune disorders (21 papers), Vasculitis and related conditions (14 papers), Autoimmune and Inflammatory Disorders Research (13 papers), interferon and immune responses (11 papers), Inflammatory Myopathies and Dermatomyositis (10 papers), Immune Cell Function and Interaction (9 papers), IgG4-Related and Inflammatory Diseases (9 papers) and Systemic Lupus Erythematosus Research (8 papers). The work is most often cited by research in Rheumatology (251 citations), Hematology (144 citations), Immunology (240 citations), Nephrology (58 citations) and Molecular Biology (313 citations). Dai Kishida has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Yasuhiro Shimojima, Yoshiki Sekijima, Shu‐ichi Ikeda, Masahide Yazaki, Masayuki Matsuda, Takanori Ichikawa, Ayako Tsuchiya‐Suzuki, Ken‐ichi Ueno, Akinori Nakamura and Wataru Ishii. Their work appears in journals such as Modern Rheumatology, The Journal of Rheumatology, Clinical Rheumatology, Clinical and Experimental Rheumatology and Frontiers in Immunology.

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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