Taketoshi Yoshida
- Artificial Intelligence top 1%
- Text and Document Classification Technologies 11
- Advanced Text Analysis Techniques 7
- Information Systems top 1%
- Spam and Phishing Detection 6
- Recommender Systems and Techniques 5
- Immunology top 5%
- T-cell and B-cell Immunology 6
- Signal Processing top 5%
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- Scheduling and Optimization Algorithms 6
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- Neonatal Respiratory Health Research 9
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- Neonatal Health and Biochemistry 6
- Co-authors
- Xijin TangWen ZhangAndreas RadbruchFalk HiepeHenrik E. MeiThomas DörnerHirokazu KaneganeQing Wang
- Partner nations
- JapanChinaUnited States
In The Last Decade
Taketoshi Yoshida
86 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 181
- Artificial Intelligence 856
- Information Systems 553
- Immunology 474
- Signal Processing 118
- Industrial and Manufacturing Engineering 89
Countries citing papers authored by Taketoshi Yoshida
This map shows the geographic impact of Taketoshi Yoshida'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 Taketoshi Yoshida with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Taketoshi Yoshida more than expected).
Fields of papers citing papers by Taketoshi Yoshida
This network shows the impact of papers produced by Taketoshi Yoshida. 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 Taketoshi Yoshida. The network helps show where Taketoshi Yoshida may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Taketoshi Yoshida, 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 | 2025 | 0 | |
| 2 | 2023 | 3 | |
| 3 | 2023 | 4 | |
| 4 | 2021 | 1 | |
| 5 | 2020 | 1 | |
| 6 | 2019 | 7 | |
| 7 | 2019 | 17 | |
| 8 | 2018 | 2 | |
| 9 | 2017 | 17 | |
| 10 | 2017 | 10 | |
| 11 | 2016 | 8 | |
| 12 | Augmented Mutual Information for Multi-word Extraction | 2009 | 11 |
| 13 | 2009 | 6 | |
| 14 | 2008 | 24 | |
| 15 | 2004 | 2 | |
| 16 | 2004 | 86 | |
| 17 | Removing capability for formaldehyde of plant growing in an activated carbon pot | 2003 | 1 |
| 18 | 2003 | 38 | |
| 19 | 2002 | 119 | |
| 20 | 2001 | 10 |
About Taketoshi Yoshida
Taketoshi Yoshida is a scholar working on Obstetrics and Gynecology, Pediatrics, Perinatology and Child Health and Information Systems, having authored 92 papers that have together received 2.6k indexed citations. Recurring topics across this work include Text and Document Classification Technologies (11 papers), Neonatal Respiratory Health Research (9 papers), Advanced Text Analysis Techniques (7 papers), Spam and Phishing Detection (6 papers), Neonatal Health and Biochemistry (6 papers), Scheduling and Optimization Algorithms (6 papers), T-cell and B-cell Immunology (6 papers) and Recommender Systems and Techniques (5 papers). The work is most often cited by research in Artificial Intelligence (856 citations), Information Systems (553 citations) and Immunology (474 citations). Taketoshi Yoshida has collaborated with scholars based in Japan, China and United States. Frequent co-authors include Xijin Tang, Wen Zhang, Wen Zhang, Andreas Radbruch, Falk Hiepe, Henrik E. Mei, Thomas Dörner, Hirokazu Kanegane, Qing Wang and Bimba F. Hoyer. Their work appears in journals such as Blood, PLoS ONE and PEDIATRICS.
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.