Aidan Gilson
- Health Informatics top 0.02%
- Radiology, Nuclear Medicine and Imaging top 2%
- Artificial Intelligence top 5%
- Family Practice top 1%
- Public Health, Environmental and Occupational Health
- Co-authors
- Richard A. TaylorLing ChiConrad SafranekThomas HuangVimig SocratesDavid ChartashUla HwangEmily A. Wang
- Topics
- Chronic Disease Management Strategies (4 papers)Machine Learning in Healthcare (3 papers)Topic Modeling (2 papers)
- Partner nations
- United StatesIrelandGermany
In The Last Decade
Aidan Gilson
11 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Health Informatics 1.1k
- Radiology, Nuclear Medicine and Imaging 533
- Artificial Intelligence 406
- Family Practice 185
- Public Health, Environmental and Occupational Health 130
Countries citing papers authored by Aidan Gilson
This map shows the geographic impact of Aidan Gilson'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 Aidan Gilson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aidan Gilson more than expected).
Fields of papers citing papers by Aidan Gilson
This network shows the impact of papers produced by Aidan Gilson. 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 Aidan Gilson. The network helps show where Aidan Gilson may publish in the future.
Co-authorship network of co-authors of Aidan Gilson
This figure shows the co-authorship network connecting the top 25 collaborators of Aidan Gilson. A scholar is included among the top collaborators of Aidan Gilson 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 Aidan Gilson. Aidan Gilson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | How Does ChatGPT Perform on the United States Medical Licensing Examination (USMLE)? The Implications of Large Language Models for Medical Education and Knowledge Assessmentbreakdown → | 1275 |
| 10 | 1 | |
| 11 | 7 | |
| 12 | 0 | |
| 13 | 2 | |
| 14 | Analysis of Health Trajectories Leading to Adverse Opioid-Related Events. | 1 |
About Aidan Gilson
Aidan Gilson is a scholar working on Health Informatics, Geriatrics and Gerontology and Family Practice, having authored 14 papers that have together received 1.3k indexed citations. Recurring topics across this work include Chronic Disease Management Strategies (4 papers), Machine Learning in Healthcare (3 papers) and Topic Modeling (2 papers). The work is most often cited by research in Health Informatics (1.1k citations), Family Practice (185 citations) and Radiology, Nuclear Medicine and Imaging (533 citations). Aidan Gilson has collaborated with scholars based in United States, Ireland and Germany. Frequent co-authors include Richard A. Taylor, Ling Chi, Conrad Safranek, Thomas Huang, Vimig Socrates, David Chartash, Ula Hwang, Emily A. Wang, Scott Levin and Lisa B. Puglisi. Their work appears in journals such as PLoS ONE, Scientific Reports and Clinical Cancer 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.