Hideyuki Arita
- Genetics top 1%
- Glioma Diagnosis and Treatment 39
- Neurology top 5%
- Cancer Research top 10%
- Cancer Genomics and Diagnostics 4
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- Radiomics and Machine Learning in Medical Imaging 10
- MRI in cancer diagnosis 4
- Medical Imaging Techniques and Applications 4
- Structural Biology top 10%
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- Meningioma and schwannoma management 15
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- Brain Metastases and Treatment 10
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- Pituitary Gland Disorders and Treatments 7
- Co-authors
- Yoshitaka NaritaKoichi IchimuraSoichiro ShibuiYasuji MiyakitaAkihiko YoshidaMakoto OhnoShintaro FukushimaYuko Matsushita
- Cited by
- GeneticsNeurologyCancer Research
- Journals
- SHILAP Revista de lepidopterología (2 papers)PLoS ONE (2 papers)The Journal of Clinical Endocrinology & Metabolism (2 papers)
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Hideyuki Arita
55 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 83
- Genetics 744
- Neurology 223
- Cancer Research 207
- Radiology, Nuclear Medicine and Imaging 276
- Structural Biology 13
Countries citing papers authored by Hideyuki Arita
This map shows the geographic impact of Hideyuki Arita'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 Hideyuki Arita with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hideyuki Arita more than expected).
Fields of papers citing papers by Hideyuki Arita
This network shows the impact of papers produced by Hideyuki Arita. 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 Hideyuki Arita. The network helps show where Hideyuki Arita may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Hideyuki Arita, 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 | 2 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 0 | |
| 6 | 2023 | 2 | |
| 7 | 2023 | 1 | |
| 8 | 2022 | 11 | |
| 9 | 2022 | 0 | |
| 10 | 2022 | 2 | |
| 11 | 2020 | 13 | |
| 12 | 2019 | 0 | |
| 13 | 2018 | 33 | |
| 14 | 2018 | 15 | |
| 15 | 2017 | 8 | |
| 16 | 2015 | 14 | |
| 17 | 2015 | 20 | |
| 18 | 2014 | 36 | |
| 19 | 2014 | 17 | |
| 20 | 2011 | 16 |
About Hideyuki Arita
Hideyuki Arita is a scholar working on Genetics, Structural Biology and Neurology, having authored 61 papers that have together received 1.1k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (39 papers), Meningioma and schwannoma management (15 papers), Brain Metastases and Treatment (10 papers), Radiomics and Machine Learning in Medical Imaging (10 papers), Pituitary Gland Disorders and Treatments (7 papers), MRI in cancer diagnosis (4 papers), Medical Imaging Techniques and Applications (4 papers) and Cancer Genomics and Diagnostics (4 papers). The work is most often cited by research in Genetics (744 citations), Neurology (223 citations) and Cancer Research (207 citations). Hideyuki Arita has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Yoshitaka Narita, Koichi Ichimura, Soichiro Shibui, Yasuji Miyakita, Akihiko Yoshida, Makoto Ohno, Shintaro Fukushima, Yuko Matsushita, Toshiki Yoshimine and Manabu Kinoshita. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Journal of Clinical Endocrinology & Metabolism.
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.