Akiko Shimauchi
- Radiology, Nuclear Medicine and Imaging top 2%
- Pathology and Forensic Medicine top 5%
- Cancer Research top 10%
- Artificial Intelligence top 10%
- Pulmonary and Respiratory Medicine
- Co-authors
- Gillian M. NewsteadHiroyuki AbéSanaz A. JansenGregory S. KarczmarYouichi MachidaRobert A. SchmidtEisuke FukumaXiaobing Fan
- Topics
- MRI in cancer diagnosis (25 papers)Advanced MRI Techniques and Applications (16 papers)Radiomics and Machine Learning in Medical Imaging (15 papers)
- Partner nations
- United StatesJapanNetherlands
In The Last Decade
Akiko Shimauchi
31 papers receiving 807 citations
Peers
Comparison fields: 5 of 51
- Radiology, Nuclear Medicine and Imaging 641
- Pathology and Forensic Medicine 289
- Cancer Research 214
- Artificial Intelligence 111
- Pulmonary and Respiratory Medicine 85
Countries citing papers authored by Akiko Shimauchi
This map shows the geographic impact of Akiko Shimauchi'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 Akiko Shimauchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akiko Shimauchi more than expected).
Fields of papers citing papers by Akiko Shimauchi
This network shows the impact of papers produced by Akiko Shimauchi. 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 Akiko Shimauchi. The network helps show where Akiko Shimauchi may publish in the future.
Co-authorship network of co-authors of Akiko Shimauchi
This figure shows the co-authorship network connecting the top 25 collaborators of Akiko Shimauchi. A scholar is included among the top collaborators of Akiko Shimauchi 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 Akiko Shimauchi. Akiko Shimauchi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 17 | |
| 2 | 6 | |
| 3 | 26 | |
| 4 | 6 | |
| 5 | 45 | |
| 6 | 18 | |
| 7 | 13 | |
| 8 | 52 | |
| 9 | 7 | |
| 10 | 16 | |
| 11 | 39 | |
| 12 | 7 | |
| 13 | 57 | |
| 14 | 30 | |
| 15 | 10 | |
| 16 | 33 | |
| 17 | 6 | |
| 18 | 11 | |
| 19 | 9 | |
| 20 | 79 |
About Akiko Shimauchi
Akiko Shimauchi is a scholar working on Radiology, Nuclear Medicine and Imaging, Pathology and Forensic Medicine and Cancer Research, having authored 31 papers that have together received 820 indexed citations. Recurring topics across this work include MRI in cancer diagnosis (25 papers), Advanced MRI Techniques and Applications (16 papers) and Radiomics and Machine Learning in Medical Imaging (15 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (641 citations), Pathology and Forensic Medicine (289 citations) and Cancer Research (214 citations). Akiko Shimauchi has collaborated with scholars based in United States, Japan and Netherlands. Frequent co-authors include Gillian M. Newstead, Hiroyuki Abé, Sanaz A. Jansen, Gregory S. Karczmar, Youichi Machida, Robert A. Schmidt, Eisuke Fukuma, Xiaobing Fan, Charlene A. Sennett and Takao Igarashi. Their work appears in journals such as Radiology, Magnetic Resonance in Medicine and American Journal of Roentgenology.
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.