Hitoshi Iyatomi
About
In The Last Decade
Hitoshi Iyatomi
83 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 115
- Oncology 2.2k
- Artificial Intelligence 1.6k
- Biomedical Engineering 610
- Epidemiology 536
- Computer Vision and Pattern Recognition 443
Countries citing papers authored by Hitoshi Iyatomi
This map shows the geographic impact of Hitoshi Iyatomi'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 Hitoshi Iyatomi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hitoshi Iyatomi more than expected).
Fields of papers citing papers by Hitoshi Iyatomi
This network shows the impact of papers produced by Hitoshi Iyatomi. 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 Hitoshi Iyatomi. The network helps show where Hitoshi Iyatomi may publish in the future.
Co-authorship network of co-authors of Hitoshi Iyatomi
This figure shows the co-authorship network connecting the top 25 collaborators of Hitoshi Iyatomi. A scholar is included among the top collaborators of Hitoshi Iyatomi 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 Hitoshi Iyatomi. Hitoshi Iyatomi 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 | 0 | |
| 3 | 9 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 15 | |
| 10 | 2 | |
| 11 | 94 | |
| 12 | 14 | |
| 13 | 30 | |
| 14 | 18 | |
| 15 | 31 | |
| 16 | 9 | |
| 17 | 60 | |
| 18 | 133 | |
| 19 | 1 | |
| 20 | Additional Learning Framework for Multipurpose Image Recognition | 2 |
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.