Keiko Niimi

2.9k total citations
79 papers, 2.0k citations indexed

About

Keiko Niimi is a scholar working on Pulmonary and Respiratory Medicine, Surgery and Gastroenterology. According to data from OpenAlex, Keiko Niimi has authored 79 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Pulmonary and Respiratory Medicine, 42 papers in Surgery and 32 papers in Gastroenterology. Recurrent topics in Keiko Niimi's work include Gastric Cancer Management and Outcomes (51 papers), Gastrointestinal Tumor Research and Treatment (24 papers) and Metastasis and carcinoma case studies (20 papers). Keiko Niimi is often cited by papers focused on Gastric Cancer Management and Outcomes (51 papers), Gastrointestinal Tumor Research and Treatment (24 papers) and Metastasis and carcinoma case studies (20 papers). Keiko Niimi collaborates with scholars based in Japan, United States and Italy. Keiko Niimi's co-authors include Mitsuhiro Fujishiro, Nobutake Yamamichi, Shinya Kodashima, Satoshi Ono, Kazuhiko Koike, Osamu Goto, Masao Omata, Chihiro Minatsuki, Yosuke Tsuji and Yoshiki Sakaguchi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Blood and Gastroenterology.

In The Last Decade

Keiko Niimi

75 papers receiving 2.0k citations

Peers

Keiko Niimi
Comparison fields: 5 of 89
  • Pulmonary and Respiratory Medicine 1.5k
  • Surgery 1.3k
  • Gastroenterology 856
  • Oncology 265
  • Epidemiology 76
Natale Di Martino Italy
Shinichi Hasegawa Japan
D. Collet France
Alan J. Cameron United States
Predrag Peško Serbia
Ryoji Ohi Japan
Risto Gullichsen Finland
Masanori Nakamura Japan
K Nakayama Japan
Natale Di Martino Italy View profile →
Citations per field, relative to Keiko Niimi
Keiko Niimi · 1×
Citations per year, relative to Keiko Niimi
Keiko Niimi · 1×

Countries citing papers authored by Keiko Niimi

Since Specialization
Citations

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

Fields of papers citing papers by Keiko Niimi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Keiko Niimi

This figure shows the co-authorship network connecting the top 25 collaborators of Keiko Niimi. A scholar is included among the top collaborators of Keiko Niimi 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 Keiko Niimi. Keiko Niimi 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
# Work Indexed citations
1 0
2 2
3 1
4 4
5 7
6
胃癌の浸潤深さを予測するための高精度人工知能システム:従来の白色光イメージング,非拡大狭帯域イメージングおよびインジゴカルミン色素コントラストイメージングの有効性【JST・京大機械翻訳】
4
7 19
8 11
9 19
10 34
11 32
12 67
13 37
14 47
15 82
16 5
17 46
18 3
19 2
20 28

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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