Kaku Tamura

2.1k citations
13 papers · 846 indexed · 1 hit paper · h-index 9

Kaku Tamura

12 papers receiving 829 citations

Hit Papers

Federated semi-supervised learning for COVID region segme...176202120262022202450100150

Peers

Kaku Tamura
Comparison fields: 5 of 98
  • Health Informatics 43
  • Infectious Diseases 542
  • General Dentistry 37
  • Modeling and Simulation 52
  • Radiology, Nuclear Medicine and Imaging 192
Replace Fangfang Yang with:
Fangfang Yang China
Lee Myers United States
Honglu Li China
Chunhua Yang China
Gamuchirai Tavaziva Canada
Ji-Peng Olivia Li United Kingdom
Ji Whae Choi China
Zhifang Cai China
Daisy Y.M. Ng Hong Kong
Carrie K.C. Wan Hong Kong
Kaku Tamura relative to Fangfang Yang China Fangfang Yang's profile →
Citations per field
00.5×6.5×
Fangfang Yang · 1×
Citations per year

Countries citing papers authored by Kaku Tamura

Since Specialization
Citations

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

Fields of papers citing papers by Kaku Tamura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

13 of 13 papers shown
#Work
1 20214
2
Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japanbreakdown →
2021176
3 202141
4 20212
5 202082
6 2020170
7 20202
8 202011
9 2020283
10 202027
11 201834
12 201714
13 20170

About Kaku Tamura

Kaku Tamura is a scholar working on Infectious Diseases, Neurology and Modeling and Simulation, having authored 13 papers that have together received 846 indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (7 papers), SARS-CoV-2 and COVID-19 Research (6 papers), COVID-19 diagnosis using AI (3 papers), SARS-CoV-2 detection and testing (3 papers), Long-Term Effects of COVID-19 (3 papers), Respiratory viral infections research (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper) and Influenza Virus Research Studies (1 paper). The work is most often cited by research in Health Informatics (43 citations), Infectious Diseases (542 citations) and General Dentistry (37 citations). Kaku Tamura has collaborated with scholars based in Japan, Italy and China. Frequent co-authors include Toshimitsu Ito, Kazuo Imai, Kazuyasu Miyoshi, Sakiko Tabata, Satoshi Mimura, Hirofumi Obinata, Yoshitaka Imoto, Yasuyuki Kato, Maki Iwata and Mayu Ikeda. Their work appears in journals such as Journal of Clinical Microbiology, The Lancet Infectious Diseases and Frontiers in Microbiology.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026