Kazuhiro Matsuo

3.4k citations
87 papers · 2.8k indexed · 1 hit paper · h-index 24

Kazuhiro Matsuo

80 papers receiving 2.7k citations

Hit Papers

Fluctuation and relaxation of macrovariables5361973202619902008100200300400500

Peers

Kazuhiro Matsuo
Comparison fields: 5 of 164
  • Statistical and Nonlinear Physics 442
  • Cardiology and Cardiovascular Medicine 541
  • Epidemiology 599
  • Physiology 447
  • Pharmacology 165
Replace Thomas S. Parker with:
Thomas S. Parker United States
Daniel Beard United States
R. Ross Netherlands
Lijian Zhang China
Hiroshi Furukawa Japan
Wenyuan Yu China
Wansheng Wang China
Aihua Hu China
Keiichi Yamamoto Japan
David Grass United States
Kazuhiro Matsuo relative to Thomas S. Parker United States Thomas S. Parker's profile →
Citations per field
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Thomas S. Parker · 1×
Citations per year

Countries citing papers authored by Kazuhiro Matsuo

Since Specialization
Citations

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

Fields of papers citing papers by Kazuhiro Matsuo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3 20241
4 20234
5 20236
6 20224
7 20215
8
Performance Maximization of In-Memory Reinforcement Learning with Variability-Controlled Hf1-xZrxO2 Ferroelectric Tunnel Junctions -- *
20201
9 20184
10 201691
11 201578
12 2014152
13 20131
14 201337
15 201310
16 20052
17
The Development of Magnetic Actuator for 24/36kV Solid Insulated Switchgear
20042
18 19990
19 199516
20
A Survey on the Parallel Genetic Algorithms
1994314

About Kazuhiro Matsuo

Kazuhiro Matsuo is a scholar working on Pharmacology, Clinical Biochemistry and Urology, having authored 87 papers that have together received 2.8k indexed citations. Recurring topics across this work include Adipokines, Inflammation, and Metabolic Diseases (11 papers), Antibiotics Pharmacokinetics and Efficacy (9 papers), Antimicrobial Resistance in Staphylococcus (7 papers), Adipose Tissue and Metabolism (6 papers), Cardiovascular Disease and Adiposity (6 papers), Ferroelectric and Negative Capacitance Devices (5 papers), Bacterial Identification and Susceptibility Testing (5 papers) and Semiconductor materials and devices (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (442 citations), Cardiology and Cardiovascular Medicine (541 citations) and Epidemiology (599 citations). Kazuhiro Matsuo has collaborated with scholars based in Japan, United States and Netherlands. Frequent co-authors include Kazuo Kitahara, Ryogo Kubo, Jongho Nang, Rei Shibata, Toyoaki Murohara, Takahiro Kambara, Noriyuki Ouchi, Daisuke Yuasa, Koji Ohashi and Yusuke Uemura. Their work appears in journals such as Journal of Biological Chemistry, Circulation and Journal of the American College of Cardiology.

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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