Ryuji Hamamoto
Impact in
- Health Informatics top 0.2%
- Molecular Biology top 1%
- Epigenetics and DNA Methylation
- Cancer-related gene regulation
- RNA modifications and cancer
- Histone Deacetylase Inhibitors Research
- Genomics and Chromatin Dynamics
Papers in
-
- Cancer Genomics and Diagnostics 14
- Cancer-related molecular mechanisms research 11
- Co-authors
- Yusuke NakamuraYoichi FurukawaFábio Pittella SilvaBruce A.J. PonderVassiliki SalouraShinya HayamiMotoko UnokiHyun‐Soo Cho
- Journals
- Biomolecules (12 papers)Oncotarget (11 papers)Neoplasia (9 papers)Cancer Science (8 papers)Scientific Reports (7 papers)
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Ryuji Hamamoto
162 papers receiving 7.3k citations
Hit Papers
Peers
Comparison fields: 5 of 175
- Health Informatics 268
- Molecular Biology 5.3k
- Cancer Research 1.1k
- Oncology 1.1k
- Radiology, Nuclear Medicine and Imaging 658
Countries citing papers authored by Ryuji Hamamoto
This map shows the geographic impact of Ryuji Hamamoto'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 Ryuji Hamamoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryuji Hamamoto more than expected).
Fields of papers citing papers by Ryuji Hamamoto
This network shows the impact of papers produced by Ryuji Hamamoto. 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 Ryuji Hamamoto. The network helps show where Ryuji Hamamoto may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ryuji Hamamoto, 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 | 2024 | 4 | |
| 2 | Comparison of Vision Transformers and Convolutional Neural Networks in Medical Image Analysis: A Systematic Review Hit paper breakdown → | 2024 | 58 |
| 3 | 2023 | 24 | |
| 4 | 2023 | 21 | |
| 5 | 2023 | 1 | |
| 6 | 2022 | 8 | |
| 7 | 2022 | 12 | |
| 8 | 2022 | 13 | |
| 9 | 2022 | 8 | |
| 10 | 2020 | 172 | |
| 11 | 2020 | 5 | |
| 12 | Unsupervised Shadow Detection for Ultrasound Images by Deep Learning | 2019 | 1 |
| 13 | 2017 | 26 | |
| 14 | 2014 | 83 | |
| 15 | 2013 | 107 | |
| 16 | 2011 | 58 | |
| 17 | 2010 | 44 | |
| 18 | 2010 | 172 | |
| 19 | 2008 | 40 | |
| 20 | 2007 | 135 |
About Ryuji Hamamoto
Ryuji Hamamoto is a scholar working on Health Informatics, Cancer Research, Molecular Biology, Radiology, Nuclear Medicine and Imaging and Oncology, having authored 169 papers that have together received 7.4k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (60 papers), Cancer-related gene regulation (49 papers), RNA modifications and cancer (33 papers), Radiomics and Machine Learning in Medical Imaging (19 papers), Cancer Genomics and Diagnostics (14 papers), Genomics and Chromatin Dynamics (13 papers), Cancer-related molecular mechanisms research (11 papers) and Ubiquitin and proteasome pathways (9 papers). The work is most often cited by research in Health Informatics (268 citations), Molecular Biology (5.3k citations), Cancer Research (1.1k citations), Oncology (1.1k citations) and Radiology, Nuclear Medicine and Imaging (658 citations). Ryuji Hamamoto has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Yusuke Nakamura, Yoichi Furukawa, Fábio Pittella Silva, Bruce A.J. Ponder, Vassiliki Saloura, Shinya Hayami, Motoko Unoki, Hyun‐Soo Cho, Helen I. Field and David E. Neal. Their work appears in journals such as Biomolecules, Oncotarget, Neoplasia, Cancer Science and Scientific Reports.
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.