David Li
- Radiology, Nuclear Medicine and Imaging top 2%
- Pathology and Forensic Medicine top 5%
- Spectroscopy top 10%
- Nuclear and High Energy Physics top 10%
- Cognitive Neuroscience
- Co-authors
- Alex L. MacKayJulian AdlerD A GraebDonald W. PatyKenneth P. WhittallAnthony TraboulseeShannon KolindCornelia Laule
- Topics
- Multiple Sclerosis Research Studies (13 papers)Advanced Neuroimaging Techniques and Applications (5 papers)Artificial Intelligence in Healthcare and Education (4 papers)
- Partner nations
- CanadaUnited StatesSwitzerland
In The Last Decade
David Li
19 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 83
- Radiology, Nuclear Medicine and Imaging 782
- Pathology and Forensic Medicine 316
- Spectroscopy 119
- Nuclear and High Energy Physics 116
- Cognitive Neuroscience 89
Countries citing papers authored by David Li
This map shows the geographic impact of David Li'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 David Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Li more than expected).
Fields of papers citing papers by David Li
This network shows the impact of papers produced by David Li. 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 David Li. The network helps show where David Li may publish in the future.
Co-authorship network of co-authors of David Li
This figure shows the co-authorship network connecting the top 25 collaborators of David Li. A scholar is included among the top collaborators of David Li 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 David Li. David Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 30 | |
| 5 | 2 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 6 | |
| 9 | 6 | |
| 10 | 17 | |
| 11 | 8 | |
| 12 | 45 | |
| 13 | 8 | |
| 14 | 21 | |
| 15 | 21 | |
| 16 | 41 | |
| 17 | 29 | |
| 18 | 15 | |
| 19 | 0 | |
| 20 | In vivo visualization of myelin water in brain by magnetic resonancebreakdown → | 756 |
About David Li
David Li is a scholar working on Health Informatics, Pathology and Forensic Medicine and Radiology, Nuclear Medicine and Imaging, having authored 22 papers that have together received 1.0k indexed citations. Recurring topics across this work include Multiple Sclerosis Research Studies (13 papers), Advanced Neuroimaging Techniques and Applications (5 papers) and Artificial Intelligence in Healthcare and Education (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (782 citations), Health Informatics (33 citations) and Pathology and Forensic Medicine (316 citations). David Li has collaborated with scholars based in Canada, United States and Switzerland. Frequent co-authors include Alex L. MacKay, Julian Adler, D A Graeb, Donald W. Paty, Kenneth P. Whittall, Anthony Traboulsee, Shannon Kolind, Cornelia Laule, Roger Tam and Irene M. Vavasour. Their work appears in journals such as Radiology, Magnetic Resonance in Medicine and American Journal of Roentgenology.
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.