John Freymann
- Health Informatics top 0.5%
- Neurology top 0.5%
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- Radiomics and Machine Learning in Medical Imaging 24
- Medical Imaging Techniques and Applications 5
- MRI in cancer diagnosis 2
- Genetics top 1%
- Glioma Diagnosis and Treatment 7
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- AI in cancer detection 6
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- Cancer Genomics and Diagnostics 4
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- Lung Cancer Diagnosis and Treatment 3
- Digital Radiography and Breast Imaging 3
- Co-authors
- Justin KirbyFred PriorKirk SmithLawrence TarboxKenneth ClarkBruce A. VendtStephen MoorePaul Koppel
- Partner nations
- United StatesUnited KingdomNetherlands
In The Last Decade
John Freymann
28 papers receiving 5.5k citations
Hit Papers
Peers
Comparison fields: 5 of 130
- Health Informatics 246
- Neurology 1.3k
- Radiology, Nuclear Medicine and Imaging 3.6k
- Computer Vision and Pattern Recognition 1.7k
- Genetics 832
Countries citing papers authored by John Freymann
This map shows the geographic impact of John Freymann'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 John Freymann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Freymann more than expected).
Fields of papers citing papers by John Freymann
This network shows the impact of papers produced by John Freymann. 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 John Freymann. The network helps show where John Freymann may publish in the future.
Co-authorship network
The 25 scholars most cited alongside John Freymann, 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 | 2 | |
| 2 | 2020 | 11 | |
| 3 | 2020 | 29 | |
| 4 | 2020 | 4 | |
| 5 | 2019 | 2 | |
| 6 | 2019 | 17 | |
| 7 | Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic featuresbreakdown → | 2017 | 1476 |
| 8 | 2017 | 93 | |
| 9 | 2017 | 48 | |
| 10 | 2015 | 90 | |
| 11 | 2015 | 53 | |
| 12 | 2015 | 69 | |
| 13 | 2015 | 54 | |
| 14 | 2014 | 59 | |
| 15 | 2014 | 177 | |
| 16 | 2014 | 76 | |
| 17 | The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repositorybreakdown → | 2013 | 2948 |
| 18 | 2012 | 114 | |
| 19 | 2012 | 13 | |
| 20 | 2011 | 64 |
About John Freymann
John Freymann is a scholar working on Radiology, Nuclear Medicine and Imaging, Structural Biology and Genetics, having authored 28 papers that have together received 5.6k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (24 papers), Glioma Diagnosis and Treatment (7 papers), AI in cancer detection (6 papers), Medical Imaging Techniques and Applications (5 papers), Cancer Genomics and Diagnostics (4 papers), Lung Cancer Diagnosis and Treatment (3 papers), Digital Radiography and Breast Imaging (3 papers) and MRI in cancer diagnosis (2 papers). The work is most often cited by research in Health Informatics (246 citations), Neurology (1.3k citations) and Radiology, Nuclear Medicine and Imaging (3.6k citations). John Freymann has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Justin Kirby, Fred Prior, Kirk Smith, Lawrence Tarbox, Kenneth Clark, Bruce A. Vendt, Stephen Moore, Paul Koppel, Michael Pringle and Aristeidis Sotiras. Their work appears in journals such as Medical Physics, Radiology, Scientific Data, Journal of Digital Imaging and Cancer.
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.