Goshi Oda
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- MRI in cancer diagnosis
- Ultrasound Imaging and Elastography
- COVID-19 diagnosis using AI
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 14
- Medical Imaging Techniques and Applications 10
- MRI in cancer diagnosis 9
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- Breast Cancer Treatment Studies 16
- Co-authors
- Tsuyoshi Nakagawa (56 shared papers)Tomoyuki Fujioka (45 shared papers)M. Mori (40 shared papers)Kazunori Kubota (36 shared papers)Ukihide Tateishi (28 shared papers)Leona Katsuta (18 shared papers)Yuka Kikuchi (10 shared papers)Yoshio Kitazume (7 shared papers)
- Journals
- Nuclear Medicine Communications (2 papers)Tomography (2 papers)Journal of Clinical Medicine (2 papers)Photodiagnosis and Photodynamic Therapy (1 paper)Annals of Oncology (1 paper)
- Partner nations
- JapanUnited StatesSweden
In The Last Decade
Goshi Oda
59 papers receiving 786 citations
Peers
Comparison fields: 5 of 92
- Health Informatics 57
- Radiology, Nuclear Medicine and Imaging 504
- Artificial Intelligence 376
- Cancer Research 91
- Neurology 49
Countries citing papers authored by Goshi Oda
This map shows the geographic impact of Goshi Oda'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 Goshi Oda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Goshi Oda more than expected).
Fields of papers citing papers by Goshi Oda
This network shows the impact of papers produced by Goshi Oda. 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 Goshi Oda. The network helps show where Goshi Oda may publish in the future.
Co-authors
The 25 scholars most cited alongside Goshi Oda, 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 63 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 136 | |
| 2 | 2020 | 63 | |
| 3 | 2020 | 50 | |
| 4 | 2020 | 45 | |
| 5 | 2012 | 41 | |
| 6 | 2019 | 38 | |
| 7 | 2020 | 38 | |
| 8 | 2020 | 31 | |
| 9 | 2022 | 29 | |
| 10 | 2020 | 25 | |
| 11 | 2019 | 24 | |
| 12 | 2021 | 23 | |
| 13 | 2022 | 20 | |
| 14 | 2020 | 19 | |
| 15 | 2019 | 16 | |
| 16 | 2018 | 13 | |
| 17 | 2022 | 13 | |
| 18 | 2021 | 11 | |
| 19 | 2015 | 10 | |
| 20 | 2021 | 10 |
About Goshi Oda
Goshi Oda is a scholar working on Radiology, Nuclear Medicine and Imaging, Cancer Research, Surgery, Oncology and Pathology and Forensic Medicine, having authored 63 papers that have together received 796 indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (16 papers), Radiomics and Machine Learning in Medical Imaging (14 papers), Breast Lesions and Carcinomas (13 papers), Medical Imaging Techniques and Applications (10 papers), MRI in cancer diagnosis (9 papers), AI in cancer detection (7 papers), Breast Implant and Reconstruction (7 papers) and Cancer Diagnosis and Treatment (6 papers). The work is most often cited by research in Health Informatics (57 citations), Radiology, Nuclear Medicine and Imaging (504 citations), Artificial Intelligence (376 citations), Cancer Research (91 citations) and Neurology (49 citations). Goshi Oda has collaborated with scholars based in Japan, United States and Sweden. Frequent co-authors include Tsuyoshi Nakagawa, Tomoyuki Fujioka, M. Mori, Kazunori Kubota, Ukihide Tateishi, Leona Katsuta, Yuka Kikuchi, Yoshio Kitazume, Toshiyuki Ishiba and Emi Yamaga. Their work appears in journals such as Nuclear Medicine Communications, Tomography, Journal of Clinical Medicine, Photodiagnosis and Photodynamic Therapy 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.