Martin D. Pickles
- Radiology, Nuclear Medicine and Imaging top 0.5%
- Pulmonary and Respiratory Medicine top 5%
- Cancer Research top 10%
- Biomedical Engineering
- Artificial Intelligence top 10%
- Co-authors
- Lindsay W. TurnbullPeter GibbsMartin LowryBachar ZelhofGary LineyGreta RodriguesD J MantonArfan Ahmed
- Topics
- MRI in cancer diagnosis (22 papers)Radiomics and Machine Learning in Medical Imaging (13 papers)Advanced Neuroimaging Techniques and Applications (6 papers)
- Partner nations
- United KingdomUnited StatesNorway
In The Last Decade
Martin D. Pickles
22 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 69
- Radiology, Nuclear Medicine and Imaging 1.7k
- Pulmonary and Respiratory Medicine 588
- Cancer Research 176
- Biomedical Engineering 126
- Artificial Intelligence 112
Countries citing papers authored by Martin D. Pickles
This map shows the geographic impact of Martin D. Pickles'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 Martin D. Pickles with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin D. Pickles more than expected).
Fields of papers citing papers by Martin D. Pickles
This network shows the impact of papers produced by Martin D. Pickles. 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 Martin D. Pickles. The network helps show where Martin D. Pickles may publish in the future.
Co-authorship network of co-authors of Martin D. Pickles
This figure shows the co-authorship network connecting the top 25 collaborators of Martin D. Pickles. A scholar is included among the top collaborators of Martin D. Pickles based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Martin D. Pickles. Martin D. Pickles is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 51 | |
| 3 | 47 | |
| 4 | 29 | |
| 5 | 20 | |
| 6 | 39 | |
| 7 | 104 | |
| 8 | 163 | |
| 9 | 26 | |
| 10 | 236 | |
| 11 | 41 | |
| 12 | 198 | |
| 13 | 87 | |
| 14 | 0 | |
| 15 | 53 | |
| 16 | 30 | |
| 17 | 124 | |
| 18 | 314 | |
| 19 | 132 | |
| 20 | 161 |
About Martin D. Pickles
Martin D. Pickles is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Cancer Research, having authored 23 papers that have together received 1.9k indexed citations. Recurring topics across this work include MRI in cancer diagnosis (22 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Advanced Neuroimaging Techniques and Applications (6 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.7k citations), Pulmonary and Respiratory Medicine (588 citations) and Cancer Research (176 citations). Martin D. Pickles has collaborated with scholars based in United Kingdom, United States and Norway. Frequent co-authors include Lindsay W. Turnbull, Peter Gibbs, Martin Lowry, Bachar Zelhof, Gary Liney, Greta Rodrigues, D J Manton, Arfan Ahmed, Muthyala Sreenivas and Sigurd Kraus. Their work appears in journals such as PLoS ONE, Nanoscale and The Journal of Urology.
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.