Xiaodan Sui
Impact in
- Ophthalmology top 5%
- Glaucoma and retinal disorders
- Retinal Diseases and Treatments
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- Retinal Imaging and Analysis
- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Retinal Imaging and Analysis 7
- Radiomics and Machine Learning in Medical Imaging 6
- Medical Imaging Techniques and Applications 2
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- Medical Image Segmentation Techniques 2
- Co-authors
- Yuanjie Zheng (14 shared papers)Shaoting Zhang (2 shared papers)Xuemei Pan (1 shared paper)Benzheng Wei (1 shared paper)Jianfeng Wu (1 shared paper)Hongsheng Bi (1 shared paper)Yanyun Jiang (9 shared papers)Hongsheng Li (1 shared paper)
- Journals
- NeuroImage (2 papers)Frontiers in Oncology (2 papers)Neurocomputing (1 paper)Medical Physics (1 paper)Electronics (1 paper)
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Xiaodan Sui
18 papers receiving 238 citations
Peers
Comparison fields: 5 of 58
- Ophthalmology 66
- Radiology, Nuclear Medicine and Imaging 128
- Computer Vision and Pattern Recognition 81
- Artificial Intelligence 49
- Health Informatics 2
Countries citing papers authored by Xiaodan Sui
This map shows the geographic impact of Xiaodan Sui'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 Xiaodan Sui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaodan Sui more than expected).
Fields of papers citing papers by Xiaodan Sui
This network shows the impact of papers produced by Xiaodan Sui. 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 Xiaodan Sui. The network helps show where Xiaodan Sui may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaodan Sui, 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 | 2017 | 111 | |
| 2 | 2021 | 47 | |
| 3 | 2018 | 19 | |
| 4 | 2022 | 8 | |
| 5 | 2022 | 8 | |
| 6 | 2023 | 8 | |
| 7 | 2022 | 7 | |
| 8 | 2020 | 7 | |
| 9 | 2023 | 6 | |
| 10 | 2018 | 4 | |
| 11 | 2020 | 4 | |
| 12 | 2024 | 3 | |
| 13 | 2021 | 3 | |
| 14 | Screening for Glaucoma from Fundus Images via Multitask Deep Learning | 2020 | 1 |
| 15 | 2025 | 1 | |
| 16 | 2024 | 1 | |
| 17 | 2024 | 1 | |
| 18 | 2024 | 1 | |
| 19 | 2025 | 0 | |
| 20 | 2021 | 0 |
About Xiaodan Sui
Xiaodan Sui is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Artificial Intelligence, Pulmonary and Respiratory Medicine and Ophthalmology, having authored 20 papers that have together received 240 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (7 papers), AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Glaucoma and retinal disorders (5 papers), Lung Cancer Diagnosis and Treatment (3 papers), Medical Imaging Techniques and Applications (2 papers), Ferroptosis and cancer prognosis (2 papers) and Medical Image Segmentation Techniques (2 papers). The work is most often cited by research in Ophthalmology (66 citations), Radiology, Nuclear Medicine and Imaging (128 citations), Computer Vision and Pattern Recognition (81 citations), Artificial Intelligence (49 citations) and Health Informatics (2 citations). Xiaodan Sui has collaborated with scholars based in China, United States and France. Frequent co-authors include Yuanjie Zheng, Shaoting Zhang, Xuemei Pan, Benzheng Wei, Jianfeng Wu, Hongsheng Bi, Yanyun Jiang, Hongsheng Li, Jie Yang and Yanhui Ding. Their work appears in journals such as NeuroImage, Frontiers in Oncology, Neurocomputing, Medical Physics and Electronics.
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.