Daisuke Kuga
Impact in
- Genetics top 2%
- Glioma Diagnosis and Treatment
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Cancer Genomics and Diagnostics
Papers in
- Genetics 46
- Glioma Diagnosis and Treatment 46
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- MicroRNA in disease regulation 7
- Cancer, Hypoxia, and Metabolism 6
- Co-authors
- Koji Yoshimoto (59 shared papers)Masahiro Mizoguchi (42 shared papers)Nobuhiro Hata (45 shared papers)Satoshi O. Suzuki (25 shared papers)Koji Iihara (29 shared papers)Ryusuke Hatae (34 shared papers)Toru Iwaki (25 shared papers)Yuhei Sangatsuda (35 shared papers)
- Journals
- Neuropathology (7 papers)World Neurosurgery (7 papers)Brain Tumor Pathology (6 papers)Neuroradiology (6 papers)Journal of Neuro-Oncology (5 papers)
- Partner nations
- JapanUnited StatesGermany
In The Last Decade
Daisuke Kuga
76 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 76
- Genetics 546
- Cancer Research 324
- Radiology, Nuclear Medicine and Imaging 170
- Neurology 109
- Molecular Biology 369
Countries citing papers authored by Daisuke Kuga
This map shows the geographic impact of Daisuke Kuga'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 Daisuke Kuga with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daisuke Kuga more than expected).
Fields of papers citing papers by Daisuke Kuga
This network shows the impact of papers produced by Daisuke Kuga. 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 Daisuke Kuga. The network helps show where Daisuke Kuga may publish in the future.
Co-authors
The 25 scholars most cited alongside Daisuke Kuga, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 88 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 169 | |
| 2 | 2016 | 97 | |
| 3 | 2017 | 70 | |
| 4 | 2012 | 62 | |
| 5 | 2016 | 41 | |
| 6 | 2021 | 40 | |
| 7 | 2014 | 36 | |
| 8 | 2016 | 34 | |
| 9 | 2021 | 31 | |
| 10 | 2016 | 31 | |
| 11 | 2019 | 30 | |
| 12 | 2018 | 30 | |
| 13 | 2008 | 29 | |
| 14 | 2011 | 26 | |
| 15 | 2018 | 26 | |
| 16 | 2021 | 25 | |
| 17 | 2017 | 20 | |
| 18 | 2020 | 19 | |
| 19 | 2011 | 19 | |
| 20 | 2024 | 18 |
About Daisuke Kuga
Daisuke Kuga is a scholar working on Genetics, Cancer Research, Radiology, Nuclear Medicine and Imaging, Neurology and Epidemiology, having authored 88 papers that have together received 1.3k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (46 papers), Meningioma and schwannoma management (10 papers), MicroRNA in disease regulation (7 papers), Neuroblastoma Research and Treatments (6 papers), Head and Neck Surgical Oncology (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Cancer, Hypoxia, and Metabolism (6 papers) and Pituitary Gland Disorders and Treatments (6 papers). The work is most often cited by research in Genetics (546 citations), Cancer Research (324 citations), Radiology, Nuclear Medicine and Imaging (170 citations), Neurology (109 citations) and Molecular Biology (369 citations). Daisuke Kuga has collaborated with scholars based in Japan, United States and Germany. Frequent co-authors include Koji Yoshimoto, Masahiro Mizoguchi, Nobuhiro Hata, Satoshi O. Suzuki, Koji Iihara, Ryusuke Hatae, Toru Iwaki, Yuhei Sangatsuda, Yojiro Akagi and Tomio Sasaki. Their work appears in journals such as Neuropathology, World Neurosurgery, Brain Tumor Pathology, Neuroradiology and Journal of Neuro-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.