Ye‐Jean Park
- Health Informatics top 1%
- Artificial Intelligence
- Radiology, Nuclear Medicine and Imaging
- Statistics, Probability and Uncertainty top 10%
- Molecular Biology
- Co-authors
- Jiawen DengEddie GuoChristopher NauglerMike PagetMehul GuptaFangwen ZhouKiyan HeybatiHarikrishnaa Ba Ramaraju
- Topics
- Artificial Intelligence in Healthcare and Education (5 papers)COVID-19 diagnosis using AI (3 papers)Machine Learning in Healthcare (2 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of the American Academy of DermatologyJournal of Medical Internet Research
- Partner nations
- CanadaUnited StatesPortugal
In The Last Decade
Ye‐Jean Park
11 papers receiving 209 citations
Hit Papers
Peers
Comparison fields: 5 of 68
- Health Informatics 98
- Artificial Intelligence 86
- Radiology, Nuclear Medicine and Imaging 35
- Statistics, Probability and Uncertainty 32
- Molecular Biology 26
Countries citing papers authored by Ye‐Jean Park
This map shows the geographic impact of Ye‐Jean Park'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 Ye‐Jean Park with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ye‐Jean Park more than expected).
Fields of papers citing papers by Ye‐Jean Park
This network shows the impact of papers produced by Ye‐Jean Park. 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 Ye‐Jean Park. The network helps show where Ye‐Jean Park may publish in the future.
Co-authorship network of co-authors of Ye‐Jean Park
This figure shows the co-authorship network connecting the top 25 collaborators of Ye‐Jean Park. A scholar is included among the top collaborators of Ye‐Jean Park 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 Ye‐Jean Park. Ye‐Jean Park is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 6 | |
| 7 | 2 | |
| 8 | Assessing the research landscape and clinical utility of large language models: a scoping reviewbreakdown → | 85 |
| 9 | 0 | |
| 10 | 0 | |
| 11 | 0 | |
| 12 | 8 | |
| 13 | 20 | |
| 14 | 81 | |
| 15 | 4 | |
| 16 | 1 |
About Ye‐Jean Park
Ye‐Jean Park is a scholar working on Health Informatics, Biological Psychiatry and Dermatology, having authored 16 papers that have together received 212 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (5 papers), COVID-19 diagnosis using AI (3 papers) and Machine Learning in Healthcare (2 papers). The work is most often cited by research in Health Informatics (98 citations), Family Practice (14 citations) and Statistics, Probability and Uncertainty (32 citations). Ye‐Jean Park has collaborated with scholars based in Canada, United States and Portugal. Frequent co-authors include Jiawen Deng, Eddie Guo, Christopher Naugler, Mike Paget, Mehul Gupta, Fangwen Zhou, Kiyan Heybati, Harikrishnaa Ba Ramaraju, Daniel Rayner and Emma Huang. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of the American Academy of Dermatology and Journal of Medical Internet Research.
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.