Meirui Jiang
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 10%
- Privacy-Preserving Technologies in Data
- AI in cancer detection
- Domain Adaptation and Few-Shot Learning
- Stochastic Gradient Optimization Techniques
Papers in
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- Privacy-Preserving Technologies in Data 5
- Domain Adaptation and Few-Shot Learning 2
- Neural Networks and Reservoir Computing 1
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- Retinal Imaging and Analysis 2
- Radiomics and Machine Learning in Medical Imaging 1
- Co-authors
- Qi Dou (7 shared papers)Zi-Rui Wang (1 shared paper)Cheng Chen (2 shared papers)Qifeng Chen (1 shared paper)Junming Chen (1 shared paper)Dong Yang (2 shared papers)An Ran Ran (1 shared paper)Vishwesh Nath (1 shared paper)
- Journals
- IEEE Transactions on Medical Imaging (2 papers)Lecture notes in computer science (1 paper)Diagnostics (1 paper)2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (1 paper)DOAJ (DOAJ: Directory of Open Access Journals) (1 paper)
In The Last Decade
Meirui Jiang
8 papers receiving 257 citations
Peers
Comparison fields: 5 of 41
- Health Informatics 27
- Artificial Intelligence 162
- Neurology 28
- Radiology, Nuclear Medicine and Imaging 74
- Computer Vision and Pattern Recognition 52
Countries citing papers authored by Meirui Jiang
This map shows the geographic impact of Meirui Jiang'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 Meirui Jiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Meirui Jiang more than expected).
Fields of papers citing papers by Meirui Jiang
This network shows the impact of papers produced by Meirui Jiang. 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 Meirui Jiang. The network helps show where Meirui Jiang may publish in the future.
Co-authors
The 25 scholars most cited alongside Meirui Jiang, 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 | 2022 | 99 | |
| 2 | 2023 | 42 | |
| 3 | 2023 | 37 | |
| 4 | 2022 | 30 | |
| 5 | 2023 | 30 | |
| 6 | 2022 | 18 | |
| 7 | 2023 | 2 | |
| 8 | 2024 | 1 | |
| 9 | 2026 | 0 |
About Meirui Jiang
Meirui Jiang is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Ophthalmology and Health Informatics, having authored 9 papers that have together received 259 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (5 papers), Retinal Imaging and Analysis (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Artificial Intelligence in Healthcare and Education (1 paper), Retinal and Optic Conditions (1 paper), Brain Tumor Detection and Classification (1 paper) and Neural Networks and Reservoir Computing (1 paper). The work is most often cited by research in Health Informatics (27 citations), Artificial Intelligence (162 citations), Neurology (28 citations), Radiology, Nuclear Medicine and Imaging (74 citations) and Computer Vision and Pattern Recognition (52 citations). Meirui Jiang has collaborated with scholars based in Hong Kong, China and Argentina. Frequent co-authors include Qi Dou, Zi-Rui Wang, Cheng Chen, Qifeng Chen, Junming Chen, Dong Yang, An Ran Ran, Vishwesh Nath, Holger R. Roth and Carol Y. Cheung. Their work appears in journals such as IEEE Transactions on Medical Imaging, Lecture notes in computer science, Diagnostics, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) and DOAJ (DOAJ: Directory of Open Access Journals).
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.