J. Raymond Geis
- Radiology, Nuclear Medicine and Imaging top 1%
- Health Informatics top 0.05%
- Artificial Intelligence top 2%
- Biomedical Engineering top 10%
- Pulmonary and Respiratory Medicine
- Co-authors
- Keith J. DreyerMarc KohliLuciano M. PrevedelloMark MichalskiRoss W. FiliceJames A. BrinkOmid KhalilzadehGarry Choy
- Topics
- Artificial Intelligence in Healthcare and Education (10 papers)Radiology practices and education (10 papers)Radiomics and Machine Learning in Medical Imaging (5 papers)
- Partner nations
- United StatesNetherlandsIreland
In The Last Decade
J. Raymond Geis
18 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Radiology, Nuclear Medicine and Imaging 1.2k
- Health Informatics 763
- Artificial Intelligence 492
- Biomedical Engineering 396
- Pulmonary and Respiratory Medicine 191
Countries citing papers authored by J. Raymond Geis
This map shows the geographic impact of J. Raymond Geis'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 J. Raymond Geis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Raymond Geis more than expected).
Fields of papers citing papers by J. Raymond Geis
This network shows the impact of papers produced by J. Raymond Geis. 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 J. Raymond Geis. The network helps show where J. Raymond Geis may publish in the future.
Co-authorship network of co-authors of J. Raymond Geis
This figure shows the co-authorship network connecting the top 25 collaborators of J. Raymond Geis. A scholar is included among the top collaborators of J. Raymond Geis 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 J. Raymond Geis. J. Raymond Geis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 22 | |
| 2 | 1 | |
| 3 | 206 | |
| 4 | 71 | |
| 5 | 73 | |
| 6 | 80 | |
| 7 | 26 | |
| 8 | Current Applications and Future Impact of Machine Learning in Radiologybreakdown → | 562 |
| 9 | 167 | |
| 10 | 35 | |
| 11 | 123 | |
| 12 | 222 | |
| 13 | 124 | |
| 14 | 30 | |
| 15 | 6 | |
| 16 | 14 | |
| 17 | 12 | |
| 18 | 12 |
About J. Raymond Geis
J. Raymond Geis is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Pharmacy, having authored 18 papers that have together received 1.8k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (10 papers), Radiology practices and education (10 papers) and Radiomics and Machine Learning in Medical Imaging (5 papers). The work is most often cited by research in Health Informatics (763 citations), Radiology, Nuclear Medicine and Imaging (1.2k citations) and Family Practice (39 citations). J. Raymond Geis has collaborated with scholars based in United States, Netherlands and Ireland. Frequent co-authors include Keith J. Dreyer, Marc Kohli, Luciano M. Prevedello, Mark Michalski, Ross W. Filice, James A. Brink, Omid Khalilzadeh, Garry Choy, Synho Do and Oleg S. Pianykh. Their work appears in journals such as Radiology, American Journal of Roentgenology and Journal of the American College of 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.