Tomoharu Kiyuna
- Biophysics top 10%
- Cell Image Analysis Techniques 4
-
- Radiomics and Machine Learning in Medical Imaging 10
- Artificial Intelligence top 10%
- AI in cancer detection 21
-
- Colorectal Cancer Screening and Detection 6
-
- Digital Imaging for Blood Diseases 7
- Image Retrieval and Classification Techniques 6
- Medical Image Segmentation Techniques 3
-
- EEG and Brain-Computer Interfaces 4
- Co-authors
- Akira SaitoHiroshi YoshidaEric CosattoYoshiko YamashitaMasahiko KurodaKosuke OikawaAtsushi OchiaiKiyoshi Mukai
- Journals
- NeuroImage (1 paper)Biochemical and Biophysical Research Communications (1 paper)Journal of Cell Science (1 paper)
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Tomoharu Kiyuna
29 papers receiving 379 citations
Peers
Comparison fields: 5 of 68
- Biophysics 36
- Radiology, Nuclear Medicine and Imaging 138
- Health Informatics 7
- Artificial Intelligence 161
- Oncology 85
Countries citing papers authored by Tomoharu Kiyuna
This map shows the geographic impact of Tomoharu Kiyuna'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 Tomoharu Kiyuna with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tomoharu Kiyuna more than expected).
Fields of papers citing papers by Tomoharu Kiyuna
This network shows the impact of papers produced by Tomoharu Kiyuna. 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 Tomoharu Kiyuna. The network helps show where Tomoharu Kiyuna may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tomoharu Kiyuna, 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 | 2 | |
| 2 | 2021 | 3 | |
| 3 | 2021 | 21 | |
| 4 | 2020 | 7 | |
| 5 | 2019 | 3 | |
| 6 | 2017 | 16 | |
| 7 | 2017 | 77 | |
| 8 | 2015 | 9 | |
| 9 | 2014 | 2 | |
| 10 | 2014 | 1 | |
| 11 | 2014 | 6 | |
| 12 | 2013 | 8 | |
| 13 | 2010 | 6 | |
| 14 | 2008 | 4 | |
| 15 | 2008 | 6 | |
| 16 | 2004 | 95 | |
| 17 | 2002 | 7 | |
| 18 | 2002 | 4 | |
| 19 | 2001 | 28 | |
| 20 | 2001 | 1 |
About Tomoharu Kiyuna
Tomoharu Kiyuna is a scholar working on Biophysics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 29 papers that have together received 396 indexed citations. Recurring topics across this work include AI in cancer detection (21 papers), Radiomics and Machine Learning in Medical Imaging (10 papers), Digital Imaging for Blood Diseases (7 papers), Colorectal Cancer Screening and Detection (6 papers), Image Retrieval and Classification Techniques (6 papers), EEG and Brain-Computer Interfaces (4 papers), Cell Image Analysis Techniques (4 papers) and Medical Image Segmentation Techniques (3 papers). The work is most often cited by research in Biophysics (36 citations), Radiology, Nuclear Medicine and Imaging (138 citations) and Health Informatics (7 citations). Tomoharu Kiyuna has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Akira Saito, Hiroshi Yoshida, Eric Cosatto, Yoshiko Yamashita, Masahiko Kuroda, Kosuke Oikawa, Atsushi Ochiai, Kiyoshi Mukai, Keiichi Yoshida and Hirokazu Taniguchi. Their work appears in journals such as NeuroImage, Biochemical and Biophysical Research Communications and Journal of Cell Science.
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.