Mariko Kawamura
- Radiology, Nuclear Medicine and Imaging top 5%
- Health Informatics top 0.5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Pulmonary and Respiratory Medicine
- Co-authors
- Taiki NozakiAkira YamadaFuminari TatsugamiDaiju UedaNoriyuki FujimaTakahiro TsuboyamaYusuke MatsuiShohei Fujita
- Topics
- Radiomics and Machine Learning in Medical Imaging (9 papers)MRI in cancer diagnosis (6 papers)Advanced X-ray and CT Imaging (4 papers)
- Partner nations
- JapanUnited States
In The Last Decade
Mariko Kawamura
15 papers receiving 461 citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Radiology, Nuclear Medicine and Imaging 231
- Health Informatics 218
- Artificial Intelligence 124
- Biomedical Engineering 61
- Pulmonary and Respiratory Medicine 49
Countries citing papers authored by Mariko Kawamura
This map shows the geographic impact of Mariko Kawamura'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 Mariko Kawamura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mariko Kawamura more than expected).
Fields of papers citing papers by Mariko Kawamura
This network shows the impact of papers produced by Mariko Kawamura. 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 Mariko Kawamura. The network helps show where Mariko Kawamura may publish in the future.
Co-authorship network of co-authors of Mariko Kawamura
This figure shows the co-authorship network connecting the top 25 collaborators of Mariko Kawamura. A scholar is included among the top collaborators of Mariko Kawamura 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 Mariko Kawamura. Mariko Kawamura is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 7 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 53 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 2 | |
| 9 | 28 | |
| 10 | 23 | |
| 11 | 14 | |
| 12 | 15 | |
| 13 | Fairness of artificial intelligence in healthcare: review and recommendationsbreakdown → | 236 |
| 14 | 25 | |
| 15 | 37 | |
| 16 | 0 | |
| 17 | 8 | |
| 18 | 19 | |
| 19 | 0 |
About Mariko Kawamura
Mariko Kawamura is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Radiation, having authored 19 papers that have together received 473 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (9 papers), MRI in cancer diagnosis (6 papers) and Advanced X-ray and CT Imaging (4 papers). The work is most often cited by research in Health Informatics (218 citations), Radiology, Nuclear Medicine and Imaging (231 citations) and Health Information Management (18 citations). Mariko Kawamura has collaborated with scholars based in Japan and United States. Frequent co-authors include Taiki Nozaki, Akira Yamada, Fuminari Tatsugami, Daiju Ueda, Noriyuki Fujima, Takahiro Tsuboyama, Yusuke Matsui, Shohei Fujita, Kenji Hirata and Rintaro Ito. Their work appears in journals such as Planetary and Space Science, Acta Dermato Venereologica and Journal of Radiation 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.