Naoto Usuyama
- Artificial Intelligence top 1%
- Molecular Biology
- Health Informatics top 0.5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Tristan NaumannHoifung Poon裕二 池谷Robert TinnJianfeng GaoHao ChengMichael LucasXiaodong Liu
- Topics
- Topic Modeling (6 papers)Biomedical Text Mining and Ontologies (4 papers)Machine Learning in Healthcare (3 papers)
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Naoto Usuyama
12 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 120
- Artificial Intelligence 867
- Molecular Biology 500
- Health Informatics 175
- Radiology, Nuclear Medicine and Imaging 124
- Computer Vision and Pattern Recognition 88
Countries citing papers authored by Naoto Usuyama
This map shows the geographic impact of Naoto Usuyama'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 Naoto Usuyama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Naoto Usuyama more than expected).
Fields of papers citing papers by Naoto Usuyama
This network shows the impact of papers produced by Naoto Usuyama. 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 Naoto Usuyama. The network helps show where Naoto Usuyama may publish in the future.
Co-authorship network of co-authors of Naoto Usuyama
This figure shows the co-authorship network connecting the top 25 collaborators of Naoto Usuyama. A scholar is included among the top collaborators of Naoto Usuyama 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 Naoto Usuyama. Naoto Usuyama 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 | 3 | |
| 3 | 1 | |
| 4 | 31 | |
| 5 | 0 | |
| 6 | 72 | |
| 7 | 14 | |
| 8 | 2 | |
| 9 | 15 | |
| 10 | 1 | |
| 11 | 5 | |
| 12 | Domain-Specific Language Model Pretraining for Biomedical Natural Language Processingbreakdown → | 1027 |
| 13 | 30 | |
| 14 | 15 |
About Naoto Usuyama
Naoto Usuyama is a scholar working on Health Informatics, Toxicology and Geriatrics and Gerontology, having authored 14 papers that have together received 1.2k indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Biomedical Text Mining and Ontologies (4 papers) and Machine Learning in Healthcare (3 papers). The work is most often cited by research in Health Informatics (175 citations), Artificial Intelligence (867 citations) and Health Information Management (53 citations). Naoto Usuyama has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Tristan Naumann, Hoifung Poon, 裕二 池谷, Robert Tinn, Jianfeng Gao, Hao Cheng, Michael Lucas, Xiaodong Liu, Xiaodong Liu and Amanda K. Hall. Their work appears in journals such as Bioinformatics, Nature Methods and Annals of Oncology.
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.