Yaniv Gur
Impact in
- Computational Mathematics top 5%
- Health Informatics top 2%
Papers in
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- Tensor decomposition and applications 4
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- Advanced Neuroimaging Techniques and Applications 13
- Advanced MRI Techniques and Applications 9
- MRI in cancer diagnosis 4
- COVID-19 diagnosis using AI 4
- Radiomics and Machine Learning in Medical Imaging 3
- Medical Imaging Techniques and Applications 2
- Co-authors
- Nir SochenOfer PasternakNathan IntratorYaniv AssafChris R. JohnsonTanveer Syeda-MahmoodEdward DiBellaDavid K. Hammond
- Journals
- IEEE Transactions on Nuclear Science (1 paper)Medical Physics (1 paper)JAMA Network Open (1 paper)Magnetic Resonance in Medicine (1 paper)Journal of Mathematical Imaging and Vision (1 paper)
- Partner nations
- United StatesIsraelCanada
In The Last Decade
Yaniv Gur
30 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 112
- Computational Mathematics 41
- Health Informatics 57
- Radiology, Nuclear Medicine and Imaging 911
- Neurology 175
- Cognitive Neuroscience 201
Countries citing papers authored by Yaniv Gur
This map shows the geographic impact of Yaniv Gur'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 Yaniv Gur with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yaniv Gur more than expected).
Fields of papers citing papers by Yaniv Gur
This network shows the impact of papers produced by Yaniv Gur. 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 Yaniv Gur. The network helps show where Yaniv Gur may publish in the future.
Co-authors
The 25 scholars most cited alongside Yaniv Gur, 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 | 2020 | 23 | |
| 2 | 2020 | 12 | |
| 3 | AI Accelerated Human-in-the-loop Structuring of Radiology Reports. | 2020 | 8 |
| 4 | 2020 | 9 | |
| 5 | 2019 | 1 | |
| 6 | 2016 | 12 | |
| 7 | 2015 | 61 | |
| 8 | 2015 | 1 | |
| 9 | A Bayesian approach to quantifying uncertainty in Tikhonov solutions for the inverse problem of electrocardiography | 2014 | 3 |
| 10 | 2014 | 4 | |
| 11 | 2014 | 11 | |
| 12 | 2014 | 5 | |
| 13 | 2014 | 59 | |
| 14 | 2013 | 34 | |
| 15 | 2013 | 4 | |
| 16 | 2012 | 25 | |
| 17 | 2011 | 18 | |
| 18 | 2011 | 13 | |
| 19 | Free water elimination and mapping from diffusion MRI Hit paper breakdown → | 2009 | 731 |
| 20 | 2009 | 5 |
About Yaniv Gur
Yaniv Gur is a scholar working on Computational Mathematics, Radiology, Nuclear Medicine and Imaging, Computer Graphics and Computer-Aided Design, Geometry and Topology and Orthopedics and Sports Medicine, having authored 31 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Neuroimaging Techniques and Applications (13 papers), Advanced MRI Techniques and Applications (9 papers), MRI in cancer diagnosis (4 papers), Tensor decomposition and applications (4 papers), COVID-19 diagnosis using AI (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Sparse and Compressive Sensing Techniques (2 papers) and Medical Imaging Techniques and Applications (2 papers). The work is most often cited by research in Computational Mathematics (41 citations), Health Informatics (57 citations), Radiology, Nuclear Medicine and Imaging (911 citations), Neurology (175 citations) and Cognitive Neuroscience (201 citations). Yaniv Gur has collaborated with scholars based in United States, Israel and Canada. Frequent co-authors include Nir Sochen, Ofer Pasternak, Nathan Intrator, Yaniv Assaf, Chris R. Johnson, Tanveer Syeda-Mahmood, Edward DiBella, David K. Hammond, Mehdi Moradi and Jeffrey S. Anderson. Their work appears in journals such as IEEE Transactions on Nuclear Science, Medical Physics, JAMA Network Open, Magnetic Resonance in Medicine and Journal of Mathematical Imaging and Vision.
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.