Shannon Kim
- General Health Professions top 10%
- Public Health, Environmental and Occupational Health
- Radiology, Nuclear Medicine and Imaging
- Education
- Clinical Psychology
- Co-authors
- Sheryl A. LarsonK. Charlie LakinDavid H. BallardAndrea HildebrandAlison ChetlenJames M. BrianElizabeth A. KrupinskiDhakshinamoorthy Ganeshan
- Topics
- Radiomics and Machine Learning in Medical Imaging (3 papers)Colorectal Cancer Screening and Detection (2 papers)Stress Responses and Cortisol (1 paper)
- Journals
- International Journal of Molecular SciencesAmerican Journal of RoentgenologyAcademic Radiology
- Partner nations
- United StatesAustraliaCanada
In The Last Decade
Shannon Kim
7 papers receiving 266 citations
Hit Papers
Peers
Comparison fields: 5 of 79
- General Health Professions 97
- Public Health, Environmental and Occupational Health 90
- Radiology, Nuclear Medicine and Imaging 88
- Education 47
- Clinical Psychology 42
Countries citing papers authored by Shannon Kim
This map shows the geographic impact of Shannon Kim'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 Shannon Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shannon Kim more than expected).
Fields of papers citing papers by Shannon Kim
This network shows the impact of papers produced by Shannon Kim. 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 Shannon Kim. The network helps show where Shannon Kim may publish in the future.
Co-authorship network of co-authors of Shannon Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Shannon Kim. A scholar is included among the top collaborators of Shannon Kim 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 Shannon Kim. Shannon Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | The Influence of Kynurenine Metabolites on Neurodegenerative Pathologiesbreakdown → | 44 |
| 2 | 1 | |
| 3 | 5 | |
| 4 | 6 | |
| 5 | 8 | |
| 6 | 118 | |
| 7 | 0 | |
| 8 | 107 |
About Shannon Kim
Shannon Kim is a scholar working on Biological Psychiatry, Behavioral Neuroscience and Radiology, Nuclear Medicine and Imaging, having authored 8 papers that have together received 289 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (3 papers), Colorectal Cancer Screening and Detection (2 papers) and Stress Responses and Cortisol (1 paper). The work is most often cited by research in Biological Psychiatry (28 citations), Health Informatics (11 citations) and General Health Professions (97 citations). Shannon Kim has collaborated with scholars based in United States, Australia and Canada. Frequent co-authors include Sheryl A. Larson, K. Charlie Lakin, David H. Ballard, Andrea Hildebrand, Alison Chetlen, James M. Brian, Elizabeth A. Krupinski, Dhakshinamoorthy Ganeshan, Tiffany L. Chan and Keyi Liu. Their work appears in journals such as International Journal of Molecular Sciences, American Journal of Roentgenology and Academic Radiology.
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.