Phil Drew
Impact in
- Cancer Research top 5%
- Breast Cancer Treatment Studies
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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
Papers in
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- Molecular Biology Techniques and Applications 3
- Gene expression and cancer classification 2
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- MRI in cancer diagnosis 3
- Radiomics and Machine Learning in Medical Imaging 3
- Co-authors
- Vicky Napp (3 shared papers)Sarah Brown (3 shared papers)Julia Brown (2 shared papers)Catherine Olivier (1 shared paper)Ian Harvey (1 shared paper)Andrew M. Hanby (1 shared paper)Lindsay W. Turnbull (1 shared paper)John Greenman (4 shared papers)
- Journals
- European Journal of Surgical Oncology (2 papers)International Journal of Oncology (2 papers)Journal of Clinical Pathology (1 paper)Journal of Clinical Oncology (1 paper)Health Technology Assessment (1 paper)
- Partner nations
- United Kingdom
In The Last Decade
Phil Drew
11 papers receiving 621 citations
Peers
Comparison fields: 5 of 71
- Cancer Research 366
- Radiology, Nuclear Medicine and Imaging 354
- Pathology and Forensic Medicine 263
- Oncology 119
- Surgery 95
Countries citing papers authored by Phil Drew
This map shows the geographic impact of Phil Drew'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 Phil Drew with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phil Drew more than expected).
Fields of papers citing papers by Phil Drew
This network shows the impact of papers produced by Phil Drew. 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 Phil Drew. The network helps show where Phil Drew may publish in the future.
Co-authors
The 25 scholars most cited alongside Phil Drew, 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 | 2010 | 442 | |
| 2 | 2010 | 62 | |
| 3 | 2006 | 56 | |
| 4 | 2002 | 38 | |
| 5 | Optimal education techniques for basic surgical trainees: lessons from education theory. | 1999 | 32 |
| 6 | 2001 | 10 | |
| 7 | 2004 | 6 | |
| 8 | 2008 | 5 | |
| 9 | 2007 | 2 | |
| 10 | 2013 | 1 | |
| 11 | 2005 | 1 |
About Phil Drew
Phil Drew is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Cancer Research, Oncology and Biotechnology, having authored 11 papers that have together received 655 indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (3 papers), MRI in cancer diagnosis (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Molecular Biology Techniques and Applications (3 papers), Cancer Research and Treatments (2 papers), Gene expression and cancer classification (2 papers), Learning Styles and Cognitive Differences (1 paper) and Heart Failure Treatment and Management (1 paper). The work is most often cited by research in Cancer Research (366 citations), Radiology, Nuclear Medicine and Imaging (354 citations), Pathology and Forensic Medicine (263 citations), Oncology (119 citations) and Surgery (95 citations). Phil Drew has collaborated with scholars based in United Kingdom. Frequent co-authors include Vicky Napp, Sarah Brown, Julia Brown, Catherine Olivier, Ian Harvey, Andrew M. Hanby, Lindsay W. Turnbull, John Greenman, Charlotte E. Dyer and Vivek Rao. Their work appears in journals such as European Journal of Surgical Oncology, International Journal of Oncology, Journal of Clinical Pathology, Journal of Clinical Oncology and Health Technology Assessment.
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.