He Sui
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
-
- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
Papers in
-
- Anomaly Detection Techniques and Applications 6
- Imbalanced Data Classification Techniques 2
- AI in cancer detection 2
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- Network Security and Intrusion Detection 4
- Co-authors
- Feng Shi (5 shared papers)Liming Xia (3 shared papers)Dinggang Shen (3 shared papers)Dijia Wu (2 shared papers)Huan Yuan (2 shared papers)Zhanhao Mo (8 shared papers)Yaozong Gao (3 shared papers)Fuhua Yan (1 shared paper)
- Journals
- Scientific Reports (2 papers)Frontiers in Endocrinology (2 papers)Information Sciences (1 paper)Future Generation Computer Systems (1 paper)IEEE Journal of Biomedical and Health Informatics (1 paper)
- Partner nations
- ChinaSouth Korea
In The Last Decade
He Sui
15 papers receiving 468 citations
Peers
Comparison fields: 5 of 89
- Health Informatics 72
- Radiology, Nuclear Medicine and Imaging 327
- Artificial Intelligence 242
- Neurology 48
- Computer Vision and Pattern Recognition 88
Countries citing papers authored by He Sui
This map shows the geographic impact of He 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 He Sui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites He Sui more than expected).
Fields of papers citing papers by He Sui
This network shows the impact of papers produced by He 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 He Sui. The network helps show where He Sui may publish in the future.
Co-authors
The 25 scholars most cited alongside He 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 | 2020 | 172 | |
| 2 | 2020 | 165 | |
| 3 | 2020 | 54 | |
| 4 | 2020 | 44 | |
| 5 | 2023 | 12 | |
| 6 | 2024 | 8 | |
| 7 | 2023 | 6 | |
| 8 | 2024 | 6 | |
| 9 | 2022 | 5 | |
| 10 | Accelerating Knee MRI: 3D Modulated Flip-Angle Technique in Refocused Imaging with an Extended Echo Train and Compressed Sensing | 2022 | 4 |
| 11 | 2023 | 4 | |
| 12 | 2024 | 4 | |
| 13 | 2025 | 1 | |
| 14 | 2023 | 1 | |
| 15 | 2025 | 1 | |
| 16 | 2024 | 0 | |
| 17 | 2024 | 0 |
About He Sui
He Sui is a scholar working on Artificial Intelligence, Computer Networks and Communications, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Epidemiology, having authored 17 papers that have together received 487 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (6 papers), Network Security and Intrusion Detection (4 papers), COVID-19 diagnosis using AI (3 papers), Imbalanced Data Classification Techniques (2 papers), AI in cancer detection (2 papers), Advanced MRI Techniques and Applications (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Thyroid Disorders and Treatments (1 paper). The work is most often cited by research in Health Informatics (72 citations), Radiology, Nuclear Medicine and Imaging (327 citations), Artificial Intelligence (242 citations), Neurology (48 citations) and Computer Vision and Pattern Recognition (88 citations). He Sui has collaborated with scholars based in China and South Korea. Frequent co-authors include Feng Shi, Liming Xia, Dinggang Shen, Dijia Wu, Huan Yuan, Zhanhao Mo, Yaozong Gao, Fuhua Yan, Changqing Zhang and Bin Song. Their work appears in journals such as Scientific Reports, Frontiers in Endocrinology, Information Sciences, Future Generation Computer Systems and IEEE Journal of Biomedical and Health Informatics.
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.