Simon Francis
Impact in
- Neurology top 10%
- Brain Tumor Detection and Classification
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- Medical Image Segmentation Techniques
- Digital Imaging for Blood Diseases
- Advanced Neural Network Applications
Papers in
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- Digital Imaging for Blood Diseases 2
- Medical Image Segmentation Techniques 2
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- Gene expression and cancer classification 1
- Co-authors
- D. Louis Collins (3 shared papers)Douglas L. Arnold (3 shared papers)Sridar Narayanan (1 shared paper)Daniel García-Lorenzo (1 shared paper)Tal Arbel (2 shared papers)Yiming Xiao (1 shared paper)Nagesh K. Subbanna (1 shared paper)Mohak Shah (1 shared paper)
- Journals
- Medical Image Analysis (2 papers)The Russian Review (1 paper)NeuroImage (1 paper)Asian Affairs (1 paper)Remote Sensing in Earth Systems Sciences (1 paper)
In The Last Decade
Simon Francis
7 papers receiving 380 citations
Peers
Comparison fields: 5 of 64
- Neurology 128
- Computer Vision and Pattern Recognition 191
- Radiology, Nuclear Medicine and Imaging 149
- Pathology and Forensic Medicine 102
- Biophysics 28
Countries citing papers authored by Simon Francis
This map shows the geographic impact of Simon Francis'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 Simon Francis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simon Francis more than expected).
Fields of papers citing papers by Simon Francis
This network shows the impact of papers produced by Simon Francis. 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 Simon Francis. The network helps show where Simon Francis may publish in the future.
Co-authors
The 13 scholars most cited alongside Simon Francis, 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 | 2012 | 246 | |
| 2 | 2010 | 116 | |
| 3 | 2006 | 28 | |
| 4 | 2024 | 3 | |
| 5 | 2020 | 2 | |
| 6 | 1972 | 2 | |
| 7 | 2009 | 1 | |
| 8 | 2009 | 0 |
About Simon Francis
Simon Francis is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology, Pathology and Forensic Medicine, Strategy and Management and Pulmonary and Respiratory Medicine, having authored 8 papers that have together received 398 indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (2 papers), Medical Image Segmentation Techniques (2 papers), Prostate Cancer Diagnosis and Treatment (1 paper), Image Processing Techniques and Applications (1 paper), Natural Resources and Economic Development (1 paper), Multiple Sclerosis Research Studies (1 paper), State Capitalism and Financial Governance (1 paper) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Neurology (128 citations), Computer Vision and Pattern Recognition (191 citations), Radiology, Nuclear Medicine and Imaging (149 citations), Pathology and Forensic Medicine (102 citations) and Biophysics (28 citations). Simon Francis has collaborated with scholars based in Canada, Sweden and India. Frequent co-authors include D. Louis Collins, Douglas L. Arnold, Sridar Narayanan, Daniel García-Lorenzo, Tal Arbel, Yiming Xiao, Nagesh K. Subbanna, Mohak Shah, Rola Harmouche and Mustafa Radha. Their work appears in journals such as Medical Image Analysis, The Russian Review, NeuroImage, Asian Affairs and Remote Sensing in Earth Systems Sciences.
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.