Sirui Ding
Impact in
- Health Informatics top 5%
-
- Advanced Neural Network Applications
Papers in
-
- Topic Modeling 6
- Machine Learning in Healthcare 3
- Natural Language Processing Techniques 2
- Adversarial Robustness in Machine Learning 1
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- Artificial Intelligence in Healthcare 2
- Co-authors
- Xia Hu (3 shared papers)Mengnan Du (1 shared paper)Zijian Zhang (1 shared paper)Piotr Mardziel (1 shared paper)Haofan Wang (1 shared paper)Zifan Wang (1 shared paper)Fan Yang (1 shared paper)Zhiyong Yuan (2 shared papers)
- Journals
- Journal of the American Medical Informatics Association (1 paper)IEEE Access (1 paper)Scientific Reports (1 paper)PubMed (2 papers)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Sirui Ding
11 papers receiving 964 citations
Sirui Ding's Hit Papers
Peers
Comparison fields: 5 of 127
- Health Informatics 44
- Computer Vision and Pattern Recognition 374
- Artificial Intelligence 492
- Radiology, Nuclear Medicine and Imaging 145
- Biophysics 39
Countries citing papers authored by Sirui Ding
This map shows the geographic impact of Sirui Ding'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 Sirui Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sirui Ding more than expected).
Fields of papers citing papers by Sirui Ding
This network shows the impact of papers produced by Sirui Ding. 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 Sirui Ding. The network helps show where Sirui Ding may publish in the future.
Co-authors
The 25 scholars most cited alongside Sirui Ding, 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 | Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks Hit paper breakdown → | 2020 | 892 |
| 2 | Large language models for disease diagnosis: a scoping review Hit paper breakdown → | 2025 | 33 |
| 3 | 2019 | 17 | |
| 4 | 2025 | 8 | |
| 5 | 2024 | 8 | |
| 6 | 2019 | 5 | |
| 7 | 2025 | 3 | |
| 8 | 2024 | 3 | |
| 9 | 2021 | 2 | |
| 10 | 2023 | 2 | |
| 11 | 2024 | 1 | |
| 12 | 2025 | 0 |
About Sirui Ding
Sirui Ding is a scholar working on Artificial Intelligence, Health Information Management, Computer Vision and Pattern Recognition, Cognitive Neuroscience and Molecular Biology, having authored 12 papers that have together received 974 indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Machine Learning in Healthcare (3 papers), Artificial Intelligence in Healthcare (2 papers), Natural Language Processing Techniques (2 papers), EEG and Brain-Computer Interfaces (2 papers), Infrastructure Resilience and Vulnerability Analysis (1 paper), Adversarial Robustness in Machine Learning (1 paper) and COVID-19 epidemiological studies (1 paper). The work is most often cited by research in Health Informatics (44 citations), Computer Vision and Pattern Recognition (374 citations), Artificial Intelligence (492 citations), Radiology, Nuclear Medicine and Imaging (145 citations) and Biophysics (39 citations). Sirui Ding has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Xia Hu, Mengnan Du, Zijian Zhang, Piotr Mardziel, Haofan Wang, Zifan Wang, Fan Yang, Zhiyong Yuan, Mingquan Lin and Jiashuo Wang. Their work appears in journals such as Journal of the American Medical Informatics Association, IEEE Access, Scientific Reports, PubMed and arXiv (Cornell University).
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.