Jaime Farley
Impact in
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- MRI in cancer diagnosis
- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- Advanced MRI Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- Modeling and Simulation top 5%
- Mathematical Biology Tumor Growth
Papers in
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- MRI in cancer diagnosis 8
- Medical Imaging Techniques and Applications 3
- Radiomics and Machine Learning in Medical Imaging 2
- Advanced MRI Techniques and Applications 2
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- Mathematical Biology Tumor Growth 3
- Co-authors
- Vandana G. Abramson (11 shared papers)Lori R. Arlinghaus (10 shared papers)Thomas E. Yankeelov (10 shared papers)Ingrid A. Mayer (7 shared papers)A. Bapsi Chakravarthy (7 shared papers)Ana M. Grau (5 shared papers)Mark C. Kelley (5 shared papers)Ingrid M. Meszoely (5 shared papers)
- Journals
- Physics in Medicine and Biology (2 papers)Magnetic Resonance in Medicine (2 papers)Journal of Clinical Oncology (1 paper)Investigative Radiology (1 paper)EJNMMI Research (1 paper)
- Partner nations
- United States
In The Last Decade
Jaime Farley
11 papers receiving 445 citations
Peers
Comparison fields: 5 of 41
- Radiology, Nuclear Medicine and Imaging 341
- Modeling and Simulation 39
- Cancer Research 53
- Oncology 33
- Health Informatics 1
Countries citing papers authored by Jaime Farley
This map shows the geographic impact of Jaime Farley'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 Jaime Farley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jaime Farley more than expected).
Fields of papers citing papers by Jaime Farley
This network shows the impact of papers produced by Jaime Farley. 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 Jaime Farley. The network helps show where Jaime Farley may publish in the future.
Co-authors
The 25 scholars most cited alongside Jaime Farley, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 130 | |
| 2 | 2013 | 97 | |
| 3 | 2013 | 58 | |
| 4 | 2011 | 55 | |
| 5 | 2011 | 35 | |
| 6 | 2014 | 33 | |
| 7 | 2011 | 26 | |
| 8 | 2012 | 11 | |
| 9 | 2013 | 2 | |
| 10 | 2013 | 1 | |
| 11 | 2014 | 1 |
About Jaime Farley
Jaime Farley is a scholar working on Radiology, Nuclear Medicine and Imaging, Modeling and Simulation, Oncology, Pulmonary and Respiratory Medicine and Cell Biology, having authored 11 papers that have together received 449 indexed citations. Recurring topics across this work include MRI in cancer diagnosis (8 papers), Mathematical Biology Tumor Growth (3 papers), Medical Imaging Techniques and Applications (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Advanced MRI Techniques and Applications (2 papers), Advanced Breast Cancer Therapies (1 paper), Breast Cancer Treatment Studies (1 paper) and Cancer Cells and Metastasis (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (341 citations), Modeling and Simulation (39 citations), Cancer Research (53 citations), Oncology (33 citations) and Health Informatics (1 citation). Jaime Farley has collaborated with scholars based in United States. Frequent co-authors include Vandana G. Abramson, Lori R. Arlinghaus, Thomas E. Yankeelov, Ingrid A. Mayer, A. Bapsi Chakravarthy, Ana M. Grau, Mark C. Kelley, Ingrid M. Meszoely, Richard G. Abramson and Melinda E. Sanders. Their work appears in journals such as Physics in Medicine and Biology, Magnetic Resonance in Medicine, Journal of Clinical Oncology, Investigative Radiology and EJNMMI 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.