Simon Graham
Impact in
- Artificial Intelligence top 0.2%
- AI in cancer detection
- Domain Adaptation and Few-Shot Learning
- Biophysics top 1%
- Cell Image Analysis Techniques
Papers in
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- AI in cancer detection 39
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- Cell Image Analysis Techniques 2
- Co-authors
- Nasir Rajpoot (33 shared papers)Shan E Ahmed Raza (16 shared papers)Quoc Dang Vu (7 shared papers)Yee Wah Tsang (2 shared papers)Ayesha S Azam (3 shared papers)Jin Tae Kwak (4 shared papers)David R. J. Snead (12 shared papers)Fayyaz Minhas (15 shared papers)
- Journals
- Medical Image Analysis (10 papers)IEEE Transactions on Medical Imaging (3 papers)Modern Pathology (2 papers)The Lancet Digital Health (2 papers)The Journal of Pathology Clinical Research (2 papers)
- Partner nations
- United KingdomEgyptUnited States
In The Last Decade
Simon Graham
44 papers receiving 3.8k citations
Simon Graham's Hit Papers
Peers
Comparison fields: 5 of 58
- Artificial Intelligence 2.7k
- Biophysics 245
- Health Informatics 38
- Computer Vision and Pattern Recognition 269
- Radiology, Nuclear Medicine and Imaging 53
Countries citing papers authored by Simon Graham
This map shows the geographic impact of Simon Graham'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 Graham with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simon Graham more than expected).
Fields of papers citing papers by Simon Graham
This network shows the impact of papers produced by Simon Graham. 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 Graham. The network helps show where Simon Graham may publish in the future.
Co-authors
The 25 scholars most cited alongside Simon Graham, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images Hit paper breakdown → | 2019 | 988 |
| 2 | A Multi-Organ Nucleus Segmentation Challenge Hit paper breakdown → | 2019 | 405 |
| 3 | 2018 | 269 | |
| 4 | 2019 | 254 | |
| 5 | 2019 | 245 | |
| 6 | 2021 | 221 | |
| 7 | 2018 | 210 | |
| 8 | 2019 | 153 | |
| 9 | 2021 | 104 | |
| 10 | 2019 | 99 | |
| 11 | 2022 | 99 | |
| 12 | 2022 | 79 | |
| 13 | 2022 | 68 | |
| 14 | 2020 | 62 | |
| 15 | 2018 | 54 | |
| 16 | 2019 | 54 | |
| 17 | 2020 | 43 | |
| 18 | 2022 | 41 | |
| 19 | 2023 | 40 | |
| 20 | 2023 | 35 |
About Simon Graham
Simon Graham is a scholar working on Artificial Intelligence, Biophysics, Cancer Research, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 44 papers that have together received 3.9k indexed citations. Recurring topics across this work include AI in cancer detection (39 papers), Cell Image Analysis Techniques (2 papers) and Breast Cancer Treatment Studies (1 paper). The work is most often cited by research in Artificial Intelligence (2.7k citations), Biophysics (245 citations), Health Informatics (38 citations), Computer Vision and Pattern Recognition (269 citations) and Radiology, Nuclear Medicine and Imaging (53 citations). Simon Graham has collaborated with scholars based in United Kingdom, Egypt and United States. Frequent co-authors include Nasir Rajpoot, Shan E Ahmed Raza, Quoc Dang Vu, Yee Wah Tsang, Ayesha S Azam, Jin Tae Kwak, David R. J. Snead, Fayyaz Minhas, Muhammad Shaban and Pheng‐Ann Heng. Their work appears in journals such as Medical Image Analysis, IEEE Transactions on Medical Imaging, Modern Pathology, The Lancet Digital Health and The Journal of Pathology Clinical 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.