Misa Sato
Impact in
- Internal Medicine top 5%
- Venous Thromboembolism Diagnosis and Management
- Condensed Matter Physics top 10%
- Micro and Nano Robotics
Papers in
-
- Topic Modeling 6
- Natural Language Processing Techniques 4
- Sentiment Analysis and Opinion Mining 2
- Advanced Text Analysis Techniques 2
- Co-authors
- Masashi Fukaya (1 shared paper)Tetsuya Iwasaki (1 shared paper)Naoto Yoshida (1 shared paper)S. David Cho (1 shared paper)Jeffrey S. Barton (1 shared paper)Jerome A. Differding (1 shared paper)Ross Anderson (1 shared paper)Samantha J. Underwood (1 shared paper)
- Journals
- Applied Microbiology and Biotechnology (1 paper)Journal of Materials Chemistry C (1 paper)Clinical & Experimental Immunology (1 paper)JAMA Surgery (1 paper)Cancer Research (1 paper)
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Misa Sato
14 papers receiving 588 citations
Peers
Comparison fields: 5 of 87
- Internal Medicine 78
- Condensed Matter Physics 76
- Biomedical Engineering 280
- Control and Systems Engineering 145
- Mechanical Engineering 184
Countries citing papers authored by Misa Sato
This map shows the geographic impact of Misa 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 Misa Sato with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Misa Sato more than expected).
Fields of papers citing papers by Misa Sato
This network shows the impact of papers produced by Misa 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 Misa Sato. The network helps show where Misa Sato may publish in the future.
Co-authors
The 25 scholars most cited alongside Misa Sato, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2002 | 317 | |
| 2 | 2014 | 118 | |
| 3 | 2009 | 73 | |
| 4 | 2015 | 24 | |
| 5 | 2013 | 19 | |
| 6 | 2015 | 16 | |
| 7 | 2015 | 10 | |
| 8 | 2013 | 8 | |
| 9 | 2017 | 7 | |
| 10 | 2016 | 6 | |
| 11 | 1984 | 6 | |
| 12 | Blind Separation of Infinitely Many Sparse Sources | 2012 | 5 |
| 13 | 2016 | 2 | |
| 14 | 2018 | 1 | |
| 15 | 2017 | 0 |
About Misa Sato
Misa Sato is a scholar working on Artificial Intelligence, Molecular Biology, Control and Systems Engineering, Information Systems and Signal Processing, having authored 15 papers that have together received 612 indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Natural Language Processing Techniques (4 papers), Blind Source Separation Techniques (2 papers), Sentiment Analysis and Opinion Mining (2 papers), Advanced Text Analysis Techniques (2 papers), Speech and Audio Processing (2 papers), Venous Thromboembolism Diagnosis and Management (1 paper) and Osteoarthritis Treatment and Mechanisms (1 paper). The work is most often cited by research in Internal Medicine (78 citations), Condensed Matter Physics (76 citations), Biomedical Engineering (280 citations), Control and Systems Engineering (145 citations) and Mechanical Engineering (184 citations). Misa Sato has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Masashi Fukaya, Tetsuya Iwasaki, Naoto Yoshida, S. David Cho, Jeffrey S. Barton, Jerome A. Differding, Ross Anderson, Samantha J. Underwood, Jennifer M. Watters and Martin A. Schreiber. Their work appears in journals such as Applied Microbiology and Biotechnology, Journal of Materials Chemistry C, Clinical & Experimental Immunology, JAMA Surgery and Cancer Research.
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.