Keita Nishimura

1.4k total citations · 1 hit paper
26 papers, 1.1k citations indexed

About

Keita Nishimura is a scholar working on Rheumatology, Epidemiology and Surgery. According to data from OpenAlex, Keita Nishimura has authored 26 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Rheumatology, 6 papers in Epidemiology and 5 papers in Surgery. Recurrent topics in Keita Nishimura's work include Streptococcal Infections and Treatments (5 papers), Rheumatoid Arthritis Research and Therapies (5 papers) and Blood transfusion and management (3 papers). Keita Nishimura is often cited by papers focused on Streptococcal Infections and Treatments (5 papers), Rheumatoid Arthritis Research and Therapies (5 papers) and Blood transfusion and management (3 papers). Keita Nishimura collaborates with scholars based in Japan and United States. Keita Nishimura's co-authors include Jung U. Yoo, Luis A. Solchaga, Victor M. Goldberg, Arnold I. Caplan, Brian Johnstone, B. Johnstone, Jinju Nishino, Sakae Tanaka, Shigeto Tohma and Akiko Komiya and has published in prestigious journals such as Journal of Bone and Joint Surgery, Gene Therapy and Journal of Immunology Research.

In The Last Decade

Keita Nishimura

26 papers receiving 1.1k citations

Hit Papers

The Chondrogenic Potential of Human Bone-Marrow-Derived M... 1998 2026 2007 2016 1998 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Keita Nishimura Japan 11 686 490 328 309 242 26 1.1k
K. Imoto Japan 9 629 0.9× 432 0.9× 529 1.6× 339 1.1× 116 0.5× 10 1.1k
José Diaz‐Romero Switzerland 12 574 0.8× 390 0.8× 365 1.1× 421 1.4× 199 0.8× 16 1.1k
T. Hennig Germany 6 876 1.3× 597 1.2× 342 1.0× 464 1.5× 228 0.9× 8 1.2k
Mercedes Alberca Spain 10 592 0.9× 778 1.6× 493 1.5× 345 1.1× 310 1.3× 16 1.8k
Karen Henshaw United Kingdom 9 563 0.8× 491 1.0× 222 0.7× 204 0.7× 138 0.6× 9 1.1k
Christoph Gaissmaier Germany 14 505 0.7× 190 0.4× 436 1.3× 258 0.8× 112 0.5× 24 970
Lynda O’Rear United States 15 365 0.5× 409 0.8× 293 0.9× 167 0.5× 593 2.5× 22 1.4k
Sarah M. Churchman United Kingdom 21 581 0.8× 511 1.0× 370 1.1× 136 0.4× 479 2.0× 36 1.6k
Marcus Mumme Switzerland 16 570 0.8× 236 0.5× 425 1.3× 243 0.8× 140 0.6× 30 1.0k
Tommi Tallheden Sweden 14 892 1.3× 309 0.6× 838 2.6× 348 1.1× 308 1.3× 18 1.6k

Countries citing papers authored by Keita Nishimura

Since Specialization
Citations

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

Fields of papers citing papers by Keita Nishimura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Keita Nishimura

This figure shows the co-authorship network connecting the top 25 collaborators of Keita Nishimura. A scholar is included among the top collaborators of Keita Nishimura based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Keita Nishimura. Keita Nishimura is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Shionoya, Hiroshi, Chiyuki Abe, Keita Nishimura, et al.. (2022). Oral and Intestinal Bacterial Substances Associated with Disease Activities in Patients with Rheumatoid Arthritis: A Cross-Sectional Clinical Study. Journal of Immunology Research. 2022. 1–13. 24 indexed citations
2.
Nishimura, Keita, et al.. (2013). Normal sequential changes in neutrophil CD64 expression after total joint arthroplasty. Journal of Orthopaedic Science. 18(6). 949–954. 14 indexed citations
4.
Doi, Tôru, Tsuyoshi Miyazaki, Jinju Nishino, et al.. (2010). Neutrophil CD64 expression as a diagnostic marker for local infection and crystal-induced arthritis. Modern Rheumatology. 20(6). 573–579. 9 indexed citations
5.
Nishino, Jinju, Sakae Tanaka, Yuho Kadono, et al.. (2010). The usefulness of neutrophil CD64 expression in the diagnosis of local infection in patients with rheumatoid arthritis in daily practice. Journal of Orthopaedic Science. 15(4). 547–552. 18 indexed citations
6.
Doi, Tôru, Tsuyoshi Miyazaki, Jinju Nishino, et al.. (2010). Neutrophil CD64 expression as a diagnostic marker for local infection and crystal-induced arthritis. Modern Rheumatology. 20(6). 573–579. 7 indexed citations
7.
Nishino, Jinju, Sakae Tanaka, Toshihiro Matsui, et al.. (2009). Prevalence of joint replacement surgery in rheumatoid arthritis patients: cross-sectional analysis in a large observational cohort in Japan. Modern Rheumatology. 19(3). 260–264. 10 indexed citations
8.
Kadono, Yuho, Sakae Tanaka, Jinju Nishino, et al.. (2009). Rheumatoid arthritis associated with osteopetrosis. Modern Rheumatology. 19(6). 687–690. 13 indexed citations
9.
Tanaka, Sakae, Jinju Nishino, Toshihiro Matsui, et al.. (2009). Neutrophil CD64 expression in the diagnosis of local musculoskeletal infection and the impact of antibiotics. Journal of Bone and Joint Surgery - British Volume. 91-B(9). 1237–1242. 23 indexed citations
10.
Nishimura, Keita, et al.. (2007). No changes in infliximab levels in blood stored for preoperative autologous blood donation. Modern Rheumatology. 18(1). 29–33. 1 indexed citations
11.
Nishimura, Keita, et al.. (2005). Measurement of articular cartilage volumes in the normal knee by magnetic resonance imaging: can cartilage volumes be estimated from physical characteristics?. Journal of Orthopaedic Science. 10(3). 246–252. 11 indexed citations
12.
Nishimura, Keita, et al.. (2005). No change of infliximab levels in stored blood for preoperative autologous blood donation: a preliminary report. Modern Rheumatology. 15(4). 302–304. 2 indexed citations
13.
Nishimura, Keita, et al.. (2005). No change of infliximab levels in stored blood for preoperative autologous blood donation: a preliminary report. Modern Rheumatology. 15(4). 302–304. 3 indexed citations
14.
Nishimura, Keita, Luis A. Solchaga, Arnold I. Caplan, et al.. (1999). Chondroprogenitor cells of synovial tissue. Arthritis & Rheumatism. 42(12). 2631–2637. 140 indexed citations
16.
Yoo, Jung U., Keita Nishimura, Luis A. Solchaga, et al.. (1998). The Chondrogenic Potential of Human Bone-Marrow-Derived Mesenchymal Progenitor Cells*. Journal of Bone and Joint Surgery. 80(12). 1745–57. 716 indexed citations breakdown →
17.
Shigematsu, Michio, Shuntaro Nagai, Keita Nishimura, et al.. (1998). Summer-type hypersensitivity pneumonitis. T-cell receptor V gene usage in BALF T-cells from 3 cases in one family.. PubMed. 15(2). 173–7. 5 indexed citations
19.
Kato, Yukari, Keitarou Suzuki, Keita Nishimura, et al.. (1981). Familial primary biliary cirrhosis. Immunological and genetic study.. PubMed. 75(3). 188–91. 17 indexed citations
20.
Kojima, Motohiro, et al.. (1973). A new method of long-term irradiation of the peripheral blood of the mouse with 32 P. Observation on the changes of lymphocytes and the thymus response by this method.. PubMed. 13(3). 193–209. 1 indexed citations

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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