Senan Doyle
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
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- Brain Tumor Detection and Classification
Papers in
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- Mobile Ad Hoc Networks 2
- Opportunistic and Delay-Tolerant Networks 2
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- Medical Image Segmentation Techniques 2
- Co-authors
- Florence Forbes (7 shared papers)Michel Dojat (6 shared papers)Christian Barillot (2 shared papers)Daniel García-Lorenzo (2 shared papers)Linda Doyle (2 shared papers)Alan Tucholka (3 shared papers)Anil Kokaram (1 shared paper)David Abrial (1 shared paper)
- Journals
- International Journal of Applied Earth Observation and Geoinformation (1 paper)Artificial Intelligence in Medicine (1 paper)Neurological Sciences (1 paper)IEEE Signal Processing Magazine (1 paper)Frontiers in Neurology (1 paper)
- Partner nations
- FranceIrelandSwitzerland
In The Last Decade
Senan Doyle
9 papers receiving 155 citations
Peers
Comparison fields: 5 of 57
- Health Informatics 11
- Neurology 17
- Radiology, Nuclear Medicine and Imaging 34
- Computer Vision and Pattern Recognition 31
- Artificial Intelligence 41
Countries citing papers authored by Senan Doyle
This map shows the geographic impact of Senan Doyle'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 Senan Doyle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Senan Doyle more than expected).
Fields of papers citing papers by Senan Doyle
This network shows the impact of papers produced by Senan Doyle. 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 Senan Doyle. The network helps show where Senan Doyle may publish in the future.
Co-authors
The 20 scholars most cited alongside Senan Doyle, 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 | 2024 | 91 | |
| 2 | 2010 | 28 | |
| 3 | 2022 | 10 | |
| 4 | A Weighted Multi-Sequence Markov Model For Brain Lesion Segmentation | 2010 | 9 |
| 5 | 2006 | 8 | |
| 6 | 2012 | 7 | |
| 7 | 2006 | 2 | |
| 8 | 2020 | 2 | |
| 9 | Automatic multiple sclerosis lesion segmentation with P-LOCUS | 2016 | 2 |
| 10 | 2022 | 0 |
About Senan Doyle
Senan Doyle is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Health Informatics, Artificial Intelligence and Analytical Chemistry, having authored 10 papers that have together received 159 indexed citations. Recurring topics across this work include Mobile Ad Hoc Networks (2 papers), Medical Image Segmentation Techniques (2 papers), Machine Learning in Healthcare (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Spectroscopy and Chemometric Analyses (2 papers), Opportunistic and Delay-Tolerant Networks (2 papers), Explainable Artificial Intelligence (XAI) (2 papers) and Forensic and Genetic Research (1 paper). The work is most often cited by research in Health Informatics (11 citations), Neurology (17 citations), Radiology, Nuclear Medicine and Imaging (34 citations), Computer Vision and Pattern Recognition (31 citations) and Artificial Intelligence (41 citations). Senan Doyle has collaborated with scholars based in France, Ireland and Switzerland. Frequent co-authors include Florence Forbes, Michel Dojat, Christian Barillot, Daniel García-Lorenzo, Linda Doyle, Alan Tucholka, Anil Kokaram, David Abrial, Lamiae Azizi and Adrian Kastler. Their work appears in journals such as International Journal of Applied Earth Observation and Geoinformation, Artificial Intelligence in Medicine, Neurological Sciences, IEEE Signal Processing Magazine and Frontiers in Neurology.
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.