Kanto Shozu

741 total citations
12 papers, 484 citations indexed

About

Kanto Shozu is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Kanto Shozu has authored 12 papers receiving a total of 484 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Radiology, Nuclear Medicine and Imaging, 3 papers in Molecular Biology and 3 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Kanto Shozu's work include Fetal and Pediatric Neurological Disorders (3 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Kanto Shozu is often cited by papers focused on Fetal and Pediatric Neurological Disorders (3 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Kanto Shozu collaborates with scholars based in Japan, United Kingdom and United States. Kanto Shozu's co-authors include Ai Dozen, Ryuji Hamamoto, Hidenori Machino, Masaaki Komatsu, Syuzo Kaneko, Ken Asada, Akira Sakai, Suguru Yasutomi, Tatsuya Arakaki and Ryu Matsuoka and has published in prestigious journals such as Cancers, Applied Sciences and Antioxidants.

In The Last Decade

Kanto Shozu

12 papers receiving 470 citations

Peers

Kanto Shozu
Comparison fields: 5 of 85
  • Radiology, Nuclear Medicine and Imaging 203
  • Artificial Intelligence 134
  • Health Informatics 115
  • Molecular Biology 81
  • Pediatrics, Perinatology and Child Health 79
Replace Ai Dozen with:
Ai Dozen Japan
Suguru Yasutomi Japan
Hidenori Machino Japan
Qianzhong Cao China
Yinhui Deng China
Mircea-Sebastian Şerbănescu Romania
Mohamed Shehata Egypt
Yijie Dong China
Ge-Ge Wu China
Jianqiao Zhou China
Ai Dozen Japan View profile →
Citations per field, relative to Kanto Shozu
Kanto Shozu · 1×
Citations per year, relative to Kanto Shozu
Kanto Shozu · 1×

Countries citing papers authored by Kanto Shozu

Since Specialization
Citations

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

Fields of papers citing papers by Kanto Shozu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kanto Shozu

This figure shows the co-authorship network connecting the top 25 collaborators of Kanto Shozu. A scholar is included among the top collaborators of Kanto Shozu 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 Kanto Shozu. Kanto Shozu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
# Work Indexed citations
1 3
2 6
3 9
4 17
5 32
6 11
7 75
8 24
9 87
10 34
11 60
12 126

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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2026