Hirofumi Obinata
- Infectious Diseases top 10%
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Neurology
- Oncology
- Co-authors
- Kaku TamuraTatsuya KodamaShuichi KawanoToshimitsu ItoSatoshi MimuraMayu IkedaKazuyasu MiyoshiManabu Kitagaki
- Topics
- COVID-19 Clinical Research Studies (6 papers)COVID-19 diagnosis using AI (4 papers)Long-Term Effects of COVID-19 (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaInternational Journal of Molecular SciencesThe Lancet Infectious Diseases
- Partner nations
- JapanUnited StatesChina
In The Last Decade
Hirofumi Obinata
15 papers receiving 483 citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Infectious Diseases 183
- Artificial Intelligence 142
- Radiology, Nuclear Medicine and Imaging 125
- Neurology 93
- Oncology 60
Countries citing papers authored by Hirofumi Obinata
This map shows the geographic impact of Hirofumi Obinata'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 Hirofumi Obinata with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hirofumi Obinata more than expected).
Fields of papers citing papers by Hirofumi Obinata
This network shows the impact of papers produced by Hirofumi Obinata. 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 Hirofumi Obinata. The network helps show where Hirofumi Obinata may publish in the future.
Co-authorship network of co-authors of Hirofumi Obinata
This figure shows the co-authorship network connecting the top 25 collaborators of Hirofumi Obinata. A scholar is included among the top collaborators of Hirofumi Obinata 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 Hirofumi Obinata. Hirofumi Obinata is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 6 | |
| 3 | 3 | |
| 4 | 5 | |
| 5 | Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japanbreakdown → | 176 |
| 6 | 2 | |
| 7 | 4 | |
| 8 | 13 | |
| 9 | 7 | |
| 10 | 170 | |
| 11 | 8 | |
| 12 | 2 | |
| 13 | 11 | |
| 14 | 27 | |
| 15 | 56 | |
| 16 | 5 | |
| 17 | 0 |
About Hirofumi Obinata
Hirofumi Obinata is a scholar working on Critical Care and Intensive Care Medicine, Neurology and Infectious Diseases, having authored 17 papers that have together received 495 indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (6 papers), COVID-19 diagnosis using AI (4 papers) and Long-Term Effects of COVID-19 (4 papers). The work is most often cited by research in Health Informatics (45 citations), Infectious Diseases (183 citations) and Modeling and Simulation (31 citations). Hirofumi Obinata has collaborated with scholars based in Japan, United States and China. Frequent co-authors include Kaku Tamura, Tatsuya Kodama, Shuichi Kawano, Toshimitsu Ito, Satoshi Mimura, Mayu Ikeda, Kazuyasu Miyoshi, Manabu Kitagaki, Sakiko Tabata and Tsutomu Kodera. Their work appears in journals such as SHILAP Revista de lepidopterología, International Journal of Molecular Sciences and The Lancet Infectious Diseases.
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.