Dejiang Xu
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
- Ophthalmology top 5%
- Retinal and Optic Conditions
- Retinal Diseases and Treatments
- Glaucoma and retinal disorders
Papers in
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- Retinal Imaging and Analysis 8
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- Visual Attention and Saliency Detection 2
- Co-authors
- Mong Li Lee (11 shared papers)Wynne Hsu (11 shared papers)Tien Yin Wong (7 shared papers)Daniel Shu Wei Ting (3 shared papers)Carol Y. Cheung (3 shared papers)Zelin Shi (4 shared papers)Yih Chung Tham (2 shared papers)Riswana Banu (1 shared paper)
In The Last Decade
Dejiang Xu
15 papers receiving 246 citations
Peers
Comparison fields: 5 of 60
- Health Informatics 22
- Ophthalmology 111
- Health Information Management 44
- Radiology, Nuclear Medicine and Imaging 158
- Nephrology 17
Countries citing papers authored by Dejiang Xu
This map shows the geographic impact of Dejiang Xu'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 Dejiang Xu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dejiang Xu more than expected).
Fields of papers citing papers by Dejiang Xu
This network shows the impact of papers produced by Dejiang Xu. 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 Dejiang Xu. The network helps show where Dejiang Xu may publish in the future.
Co-authors
The 25 scholars most cited alongside Dejiang Xu, 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 | 152 | |
| 2 | 2022 | 26 | |
| 3 | 2019 | 20 | |
| 4 | 2022 | 11 | |
| 5 | 2012 | 11 | |
| 6 | 2013 | 8 | |
| 7 | 2012 | 5 | |
| 8 | 2019 | 5 | |
| 9 | 2023 | 3 | |
| 10 | Artificial Intelligence Deep Learning System for Predicting Chronic Kidney Disease from Retinal Images | 2019 | 3 |
| 11 | 2024 | 2 | |
| 12 | 2019 | 2 | |
| 13 | 2018 | 2 | |
| 14 | 2021 | 1 | |
| 15 | 2013 | 1 |
About Dejiang Xu
Dejiang Xu is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Ophthalmology, Aerospace Engineering and Media Technology, having authored 15 papers that have together received 252 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (8 papers), Retinal and Optic Conditions (6 papers), Infrared Target Detection Methodologies (4 papers), Advanced Image Fusion Techniques (3 papers), Retinal Diseases and Treatments (3 papers), Glaucoma and retinal disorders (2 papers), Visual Attention and Saliency Detection (2 papers) and Adversarial Robustness in Machine Learning (2 papers). The work is most often cited by research in Health Informatics (22 citations), Ophthalmology (111 citations), Health Information Management (44 citations), Radiology, Nuclear Medicine and Imaging (158 citations) and Nephrology (17 citations). Dejiang Xu has collaborated with scholars based in Singapore, China and Hong Kong. Frequent co-authors include Mong Li Lee, Wynne Hsu, Tien Yin Wong, Daniel Shu Wei Ting, Carol Y. Cheung, Zelin Shi, Yih Chung Tham, Riswana Banu, Ching‐Yu Cheng and Jost B. Jonas. Their work appears in journals such as Brain Communications, BMJ Open, IEEE Transactions on Image Processing, The Lancet Digital Health and American Journal of Ophthalmology.
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.