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
- Semantic Web and Ontologies 1
-
- Artificial Intelligence in Healthcare 2
- Co-authors
- Xia Hu (3 shared papers)Zijian Zhang (1 shared paper)Haofan Wang (1 shared paper)Piotr Mardziel (1 shared paper)Fan Yang (1 shared paper)Zifan Wang (1 shared paper)Mengnan Du (1 shared paper)Zhiyong Yuan (2 shared papers)
- Journals
- IEEE Access (1 paper)Scientific Reports (1 paper)arXiv (Cornell University) (1 paper)PubMed (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Sirui Ding
10 papers receiving 813 citations
Sirui Ding's Hit Papers
Peers
Comparison fields: 5 of 124
- Health Informatics 43
- Computer Vision and Pattern Recognition 320
- Artificial Intelligence 422
- Radiology, Nuclear Medicine and Imaging 138
- Biophysics 33
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 | 759 |
| 2 | Large language models for disease diagnosis: a scoping review Hit paper breakdown → | 2025 | 19 |
| 3 | 2019 | 17 | |
| 4 | 2024 | 6 | |
| 5 | 2025 | 6 | |
| 6 | 2025 | 3 | |
| 7 | 2024 | 3 | |
| 8 | 2019 | 3 | |
| 9 | 2021 | 2 | |
| 10 | 2023 | 2 | |
| 11 | 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 11 papers that have together received 820 indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Machine Learning in Healthcare (3 papers), Natural Language Processing Techniques (2 papers), Artificial Intelligence in Healthcare (2 papers), EEG and Brain-Computer Interfaces (2 papers), Evacuation and Crowd Dynamics (1 paper), Semantic Web and Ontologies (1 paper) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Health Informatics (43 citations), Computer Vision and Pattern Recognition (320 citations), Artificial Intelligence (422 citations), Radiology, Nuclear Medicine and Imaging (138 citations) and Biophysics (33 citations). Sirui Ding has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Xia Hu, Zijian Zhang, Haofan Wang, Piotr Mardziel, Fan Yang, Zifan Wang, Mengnan Du, Zhiyong Yuan, Jianhui Zhao and Jiancheng Ye. Their work appears in journals such as IEEE Access, Scientific Reports, arXiv (Cornell University) and PubMed.
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.