Gen Sato

22 papers receiving 432 citations

Peers

Gen Sato
Comparison fields: 5 of 79
  • Cellular and Molecular Neuroscience 275
  • Neurology 103
  • Developmental Neuroscience 41
  • Physiology 28
  • Gastroenterology 16
Replace Zhenjun Tan with:
Zhenjun Tan United States
Cordula Rakers Germany
Niamh Murphy Ireland
Akito Nakao Japan
Ervin Horváth Germany
Seongeun Cho United States
Gilles Bru‐Mercier United Kingdom
Emi Iwata Japan
Tobias E. Karlsson Sweden
Juan Zhao China
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Citations per year

Countries citing papers authored by Gen Sato

Since Specialization
Citations

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

Fields of papers citing papers by Gen Sato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1986162
2 198798
3 198765
4 196150
5 199914
6 196212
7 20218
8 20007
9
A Handwritten Character Recognition System by Efficient Combination of Multiple Classifiers
19966
10 19625
11 19924
12 19814
13 20242
14 20212
15 20242
16 20242
17 19862
18 19962
19
149. Changes of Diet in the Families with Hypertensive Patients and on the Stroke Death at the Rural Area in Akita from 1950 to 1967
19691
20 20201

About Gen Sato

Gen Sato is a scholar working on Computer Vision and Pattern Recognition, Pathology and Forensic Medicine, Cellular and Molecular Neuroscience, Oncology and Signal Processing, having authored 26 papers that have together received 451 indexed citations. Recurring topics across this work include Speech and Audio Processing (3 papers), Neuroscience and Neuropharmacology Research (3 papers), COVID-19 diagnosis using AI (2 papers), Animal testing and alternatives (2 papers), Advanced Neural Network Applications (2 papers), Pancreatic and Hepatic Oncology Research (2 papers), Lung Cancer Treatments and Mutations (2 papers) and Diet and metabolism studies (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (275 citations), Neurology (103 citations), Developmental Neuroscience (41 citations), Physiology (28 citations) and Gastroenterology (16 citations). Gen Sato has collaborated with scholars based in Japan, United States and Germany. Frequent co-authors include Kyuya Kogure, Hiroshi Onodera, Takesi HUKUHARA, Kazuo Tsukidate, Fumio Sagami, Satoru Hosokawa, Makoto Yoshizawa, Hideaki Takeda, Y. Nakajima and Shoji Asakura. Their work appears in journals such as International Journal of Computer Assisted Radiology and Surgery, Mutation Research/Genetic Toxicology and Environmental Mutagenesis, Brain Research, Japanese Journal of Clinical Oncology and Journal of Cerebral Blood Flow & Metabolism.

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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