David Snead
Impact in
- Health Informatics top 0.5%
-
- Radiomics and Machine Learning in Medical Imaging
Papers in
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- AI in cancer detection 43
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- Radiomics and Machine Learning in Medical Imaging 22
- Retinal and Macular Surgery 11
- Co-authors
- Nasir Rajpoot (40 shared papers)Korsuk Sirinukunwattana (9 shared papers)Ian A. Cree (10 shared papers)Shan E Ahmed Raza (14 shared papers)Yee‐Wah Tsang (3 shared papers)Arthur Weltman (14 shared papers)Sean James (11 shared papers)Richard L. Seip (13 shared papers)
- Journals
- International Journal of Sports Medicine (8 papers)Eye (8 papers)Histopathology (7 papers)Modern Pathology (5 papers)Scientific Reports (4 papers)
- Partner nations
- United KingdomUnited StatesQatar
In The Last Decade
David Snead
125 papers receiving 6.4k citations
David Snead's Hit Papers
Peers
Comparison fields: 5 of 168
- Health Informatics 181
- Radiology, Nuclear Medicine and Imaging 2.3k
- Biophysics 497
- Artificial Intelligence 2.4k
- Computer Vision and Pattern Recognition 1.2k
Countries citing papers authored by David Snead
This map shows the geographic impact of David Snead'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 David Snead with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Snead more than expected).
Fields of papers citing papers by David Snead
This network shows the impact of papers produced by David Snead. 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 David Snead. The network helps show where David Snead may publish in the future.
Co-authors
The 25 scholars most cited alongside David Snead, 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 128 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images Hit paper breakdown → | 2016 | 826 |
| 2 | Gland segmentation in colon histology images: The glas challenge contest Hit paper breakdown → | 2016 | 570 |
| 3 | 2004 | 387 | |
| 4 | 1997 | 336 | |
| 5 | 2018 | 217 | |
| 6 | 2007 | 184 | |
| 7 | 2015 | 171 | |
| 8 | 2015 | 168 | |
| 9 | 2015 | 165 | |
| 10 | 2007 | 163 | |
| 11 | 1990 | 160 | |
| 12 | 1995 | 152 | |
| 13 | 2021 | 150 | |
| 14 | 2019 | 149 | |
| 15 | 2008 | 109 | |
| 16 | 2017 | 105 | |
| 17 | 1991 | 102 | |
| 18 | 2020 | 101 | |
| 19 | 2009 | 82 | |
| 20 | 2007 | 75 |
About David Snead
David Snead is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Oncology, Pulmonary and Respiratory Medicine and Molecular Biology, having authored 128 papers that have together received 6.6k indexed citations. Recurring topics across this work include AI in cancer detection (43 papers), Radiomics and Machine Learning in Medical Imaging (22 papers), Colorectal Cancer Screening and Detection (14 papers), Sports Performance and Training (12 papers), Cardiovascular and exercise physiology (11 papers), Retinal and Macular Surgery (11 papers), Intraocular Surgery and Lenses (9 papers) and Cancer Genomics and Diagnostics (8 papers). The work is most often cited by research in Health Informatics (181 citations), Radiology, Nuclear Medicine and Imaging (2.3k citations), Biophysics (497 citations), Artificial Intelligence (2.4k citations) and Computer Vision and Pattern Recognition (1.2k citations). David Snead has collaborated with scholars based in United Kingdom, United States and Qatar. Frequent co-authors include Nasir Rajpoot, Korsuk Sirinukunwattana, Ian A. Cree, Shan E Ahmed Raza, Yee‐Wah Tsang, Arthur Weltman, Sean James, Richard L. Seip, Martin P. Snead and Simon Graham. Their work appears in journals such as International Journal of Sports Medicine, Eye, Histopathology, Modern Pathology and Scientific Reports.
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.