Shuang Di
- Artificial Intelligence top 10%
- Epidemiology
- Health Informatics top 2%
- Cardiology and Cardiovascular Medicine
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Jeremy PetchWalter NelsonMichael McGillionP.J. DevereauxNeil G. BarrJon-David SchwalmTej ShethMadhu K. Natarajan
- Topics
- Machine Learning in Healthcare (2 papers)Cardiac Imaging and Diagnostics (2 papers)Artificial Intelligence in Healthcare and Education (2 papers)
- Journals
- Nature CommunicationsSHILAP Revista de lepidopterologíaScientific Reports
- Partner nations
- CanadaUnited StatesChina
In The Last Decade
Shuang Di
12 papers receiving 436 citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Artificial Intelligence 143
- Epidemiology 78
- Health Informatics 71
- Cardiology and Cardiovascular Medicine 63
- Radiology, Nuclear Medicine and Imaging 61
Countries citing papers authored by Shuang Di
This map shows the geographic impact of Shuang Di'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 Shuang Di with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuang Di more than expected).
Fields of papers citing papers by Shuang Di
This network shows the impact of papers produced by Shuang Di. 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 Shuang Di. The network helps show where Shuang Di may publish in the future.
Co-authorship network of co-authors of Shuang Di
This figure shows the co-authorship network connecting the top 25 collaborators of Shuang Di. A scholar is included among the top collaborators of Shuang Di based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shuang Di. Shuang Di is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 13 | |
| 4 | 8 | |
| 5 | 6 | |
| 6 | 1 | |
| 7 | 6 | |
| 8 | 10 | |
| 9 | Opening the Black Box: The Promise and Limitations of Explainable Machine Learning in Cardiologybreakdown → | 316 |
| 10 | 77 | |
| 11 | Stepping Out: Chinese Immigrants in The Canadian Wilderness A Qualitative Study of Recent Chinese Immigrants’ Outdoor Recreation Experiences in Canada | 1 |
| 12 | 1 |
About Shuang Di
Shuang Di is a scholar working on Health Informatics, Tourism, Leisure and Hospitality Management and Statistics and Probability, having authored 12 papers that have together received 442 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (2 papers), Cardiac Imaging and Diagnostics (2 papers) and Artificial Intelligence in Healthcare and Education (2 papers). The work is most often cited by research in Health Informatics (71 citations), Health Information Management (48 citations) and Artificial Intelligence (143 citations). Shuang Di has collaborated with scholars based in Canada, United States and China. Frequent co-authors include Jeremy Petch, Walter Nelson, Michael McGillion, P.J. Devereaux, Neil G. Barr, Jon-David Schwalm, Tej Sheth, Madhu K. Natarajan, Laura C. Rosella and Hertzel C. Gerstein. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and Scientific Reports.
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.