Ran Gu
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- Breast Lesions and Carcinomas 11
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- AI in cancer detection 7
- Domain Adaptation and Few-Shot Learning 3
- Co-authors
- Guotai Wang (9 shared papers)Shaoting Zhang (6 shared papers)Wenhui Lei (5 shared papers)Kang Li (3 shared papers)Jingyang Zhang (4 shared papers)Shichuan Zhang (3 shared papers)Fengtao Liu (8 shared papers)Yaping Yang (11 shared papers)
- Journals
- IEEE Transactions on Medical Imaging (4 papers)BMC Cancer (2 papers)Journal of Surgical Research (2 papers)European Radiology (2 papers)Neurocomputing (2 papers)
- Partner nations
- ChinaUnited StatesSwitzerland
In The Last Decade
Ran Gu
26 papers receiving 325 citations
Peers
Comparison fields: 5 of 63
- Health Informatics 9
- Radiology, Nuclear Medicine and Imaging 136
- Computer Vision and Pattern Recognition 113
- Artificial Intelligence 122
- Neurology 28
Countries citing papers authored by Ran Gu
This map shows the geographic impact of Ran Gu'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 Ran Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ran Gu more than expected).
Fields of papers citing papers by Ran Gu
This network shows the impact of papers produced by Ran Gu. 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 Ran Gu. The network helps show where Ran Gu may publish in the future.
Co-authors
The 25 scholars most cited alongside Ran Gu, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 36 | |
| 2 | 2023 | 28 | |
| 3 | 2012 | 27 | |
| 4 | 2021 | 26 | |
| 5 | 2023 | 24 | |
| 6 | 2023 | 24 | |
| 7 | 2015 | 21 | |
| 8 | 2021 | 21 | |
| 9 | 2021 | 20 | |
| 10 | 2023 | 18 | |
| 11 | 2022 | 14 | |
| 12 | 2018 | 14 | |
| 13 | 2019 | 8 | |
| 14 | 2019 | 8 | |
| 15 | 2017 | 7 | |
| 16 | 2021 | 7 | |
| 17 | 2023 | 5 | |
| 18 | 2024 | 5 | |
| 19 | 2017 | 4 | |
| 20 | 2019 | 3 |
About Ran Gu
Ran Gu is a scholar working on Pathology and Forensic Medicine, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Cancer Research and Oncology, having authored 30 papers that have together received 328 indexed citations. Recurring topics across this work include Breast Lesions and Carcinomas (11 papers), Breast Cancer Treatment Studies (7 papers), AI in cancer detection (7 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Medical Image Segmentation Techniques (4 papers), Advanced Neural Network Applications (3 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Global Cancer Incidence and Screening (3 papers). The work is most often cited by research in Health Informatics (9 citations), Radiology, Nuclear Medicine and Imaging (136 citations), Computer Vision and Pattern Recognition (113 citations), Artificial Intelligence (122 citations) and Neurology (28 citations). Ran Gu has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include Guotai Wang, Shaoting Zhang, Wenhui Lei, Kang Li, Jingyang Zhang, Shichuan Zhang, Fengtao Liu, Yaping Yang, Fengxi Su and Qiang Liu. Their work appears in journals such as IEEE Transactions on Medical Imaging, BMC Cancer, Journal of Surgical Research, European Radiology and Neurocomputing.
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.