Robert J. Gillies
- Radiology, Nuclear Medicine and Imaging top 0.01%
- Radiomics and Machine Learning in Medical Imaging 138
- MRI in cancer diagnosis 54
- Advanced MRI Techniques and Applications 52
- Medical Imaging Techniques and Applications 44
- Health Informatics top 0.02%
- Cancer Research top 0.02%
- Cancer, Hypoxia, and Metabolism 93
- Pulmonary and Respiratory Medicine top 0.05%
- Lung Cancer Diagnosis and Treatment 66
- Modeling and Simulation top 0.1%
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- ATP Synthase and ATPases Research 34
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- AI in cancer detection 34
- Co-authors
- Robert A. GatenbyPaul E. KinahanHedvig HricakHugo J.W.L. AertsAndré DekkerNatarajan RaghunandPhilippe LambinRalph T. H. Leijenaar
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Robert J. Gillies
513 papers receiving 56.1k citations
Hit Papers
Peers
Comparison fields: 5 of 206
- Radiology, Nuclear Medicine and Imaging 28.0k
- Health Informatics 1.1k
- Cancer Research 11.5k
- Pulmonary and Respiratory Medicine 12.0k
- Modeling and Simulation 1.6k
Countries citing papers authored by Robert J. Gillies
This map shows the geographic impact of Robert J. Gillies'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 Robert J. Gillies with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert J. Gillies more than expected).
Fields of papers citing papers by Robert J. Gillies
This network shows the impact of papers produced by Robert J. Gillies. 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 Robert J. Gillies. The network helps show where Robert J. Gillies may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Robert J. Gillies, 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 | 2021 | 91 | |
| 2 | 2021 | 31 | |
| 3 | 2020 | 15 | |
| 4 | 2019 | 66 | |
| 5 | 2018 | 34 | |
| 6 | 2017 | 89 | |
| 7 | Somatic Mutations Drive Distinct Imaging Phenotypes in Lung Cancerbreakdown → | 2017 | 304 |
| 8 | Neutralization of Tumor Acidity Improves Antitumor Responses to Immunotherapybreakdown → | 2016 | 468 |
| 9 | 2015 | 211 | |
| 10 | 2015 | 119 | |
| 11 | Acidity Generated by the Tumor Microenvironment Drives Local Invasionbreakdown → | 2013 | 1065 |
| 12 | 2012 | 200 | |
| 13 | 2012 | 111 | |
| 14 | 2010 | 45 | |
| 15 | Adaptive Therapybreakdown → | 2009 | 557 |
| 16 | 2009 | 171 | |
| 17 | 2009 | 46 | |
| 18 | 2009 | 222 | |
| 19 | Bicarbonate Increases Tumor pH and Inhibits Spontaneous Metastasesbreakdown → | 2009 | 524 |
| 20 | 2008 | 20 |
About Robert J. Gillies
Robert J. Gillies is a scholar working on Radiology, Nuclear Medicine and Imaging, Cancer Research and Modeling and Simulation, having authored 515 papers that have together received 57.0k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (138 papers), Cancer, Hypoxia, and Metabolism (93 papers), Lung Cancer Diagnosis and Treatment (66 papers), MRI in cancer diagnosis (54 papers), Advanced MRI Techniques and Applications (52 papers), Medical Imaging Techniques and Applications (44 papers), ATP Synthase and ATPases Research (34 papers) and AI in cancer detection (34 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (28.0k citations), Health Informatics (1.1k citations) and Cancer Research (11.5k citations). Robert J. Gillies has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Robert A. Gatenby, Paul E. Kinahan, Hedvig Hricak, Hugo J.W.L. Aerts, André Dekker, Natarajan Raghunand, Philippe Lambin, Ralph T. H. Leijenaar, Sara Carvalho and Jonathan W. Wojtkowiak. Their work appears in journals such as Science, Cell and Proceedings of the National Academy of Sciences.
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.