裕二 池谷
- 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 PoonNaoto UsuyamaRobert TinnHao ChengJianfeng GaoMichael LucasXiaodong Liu
- Topics
- Topic Modeling (10 papers)Biomedical Text Mining and Ontologies (8 papers)Machine Learning in Healthcare (5 papers)
- Partner nations
- United StatesChinaCanada
In The Last Decade
裕二 池谷
16 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 129
- Artificial Intelligence 948
- Molecular Biology 534
- Health Informatics 175
- Radiology, Nuclear Medicine and Imaging 122
- Computer Vision and Pattern Recognition 90
Countries citing papers authored by 裕二 池谷
This map shows the geographic impact of 裕二 池谷'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 裕二 池谷 with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites 裕二 池谷 more than expected).
Fields of papers citing papers by 裕二 池谷
This network shows the impact of papers produced by 裕二 池谷. 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 裕二 池谷. The network helps show where 裕二 池谷 may publish in the future.
Co-authorship network of co-authors of 裕二 池谷
This figure shows the co-authorship network connecting the top 25 collaborators of 裕二 池谷. A scholar is included among the top collaborators of 裕二 池谷 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 裕二 池谷. 裕二 池谷 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 | 4 | |
| 3 | 1 | |
| 4 | 31 | |
| 5 | 3 | |
| 6 | 72 | |
| 7 | 0 | |
| 8 | 6 | |
| 9 | 17 | |
| 10 | 15 | |
| 11 | 3 | |
| 12 | 15 | |
| 13 | 4 | |
| 14 | Domain-Specific Language Model Pretraining for Biomedical Natural Language Processingbreakdown → | 1027 |
| 15 | 10 | |
| 16 | 30 | |
| 17 | 44 | |
| 18 | 24 | |
| 19 | 5 |
About 裕二 池谷
裕二 池谷 is a scholar working on Artificial Intelligence, Family Practice and Neurology, having authored 19 papers that have together received 1.3k indexed citations. Recurring topics across this work include Topic Modeling (10 papers), Biomedical Text Mining and Ontologies (8 papers) and Machine Learning in Healthcare (5 papers). The work is most often cited by research in Health Informatics (175 citations), Artificial Intelligence (948 citations) and Health Information Management (64 citations) 裕二 池谷 has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Tristan Naumann, Hoifung Poon, Naoto Usuyama, Robert Tinn, Hao Cheng, Jianfeng Gao, Michael Lucas, Xiaodong Liu, Yuan Gao and Zhiyong Sun. Their work appears in journals such as Nature Methods, Journal of Materials Chemistry A and Sensors and Actuators B Chemical.
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.