Ruida Cheng
Impact in
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
Papers in
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- Medical Image Segmentation Techniques 9
- Advanced Neural Network Applications 7
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- Medical Imaging and Analysis 4
- Lower Extremity Biomechanics and Pathologies 2
- Co-authors
- Evan McCreedy (13 shared papers)Matthew McAuliffe (14 shared papers)William Gandler (11 shared papers)Barış Türkbey (8 shared papers)Peter L. Choyke (8 shared papers)Ronald M. Summers (5 shared papers)Holger R. Roth (5 shared papers)Le Lü (4 shared papers)
- Journals
- Medical Physics (1 paper)Magnetic Resonance in Medicine (1 paper)Journal of Vascular and Interventional Radiology (1 paper)Journal of Medical Imaging (2 papers)Zenodo (CERN European Organization for Nuclear Research) (1 paper)
- Partner nations
- United StatesAustraliaNetherlands
In The Last Decade
Ruida Cheng
12 papers receiving 305 citations
Peers
Comparison fields: 5 of 71
- Health Informatics 8
- Computer Vision and Pattern Recognition 94
- Radiology, Nuclear Medicine and Imaging 106
- Radiation 34
- Hepatology 26
Countries citing papers authored by Ruida Cheng
This map shows the geographic impact of Ruida Cheng'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 Ruida Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ruida Cheng more than expected).
Fields of papers citing papers by Ruida Cheng
This network shows the impact of papers produced by Ruida Cheng. 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 Ruida Cheng. The network helps show where Ruida Cheng may publish in the future.
Co-authors
The 25 scholars most cited alongside Ruida Cheng, 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 | 2007 | 111 | |
| 2 | 2017 | 55 | |
| 3 | 2016 | 38 | |
| 4 | 2019 | 32 | |
| 5 | 2019 | 18 | |
| 6 | 2017 | 17 | |
| 7 | 2014 | 15 | |
| 8 | 2021 | 9 | |
| 9 | 2017 | 9 | |
| 10 | 2013 | 2 | |
| 11 | 2016 | 2 | |
| 12 | 2008 | 1 | |
| 13 | 2012 | 0 | |
| 14 | 2013 | 0 |
About Ruida Cheng
Ruida Cheng is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering, Pulmonary and Respiratory Medicine, Endocrinology, Diabetes and Metabolism and Computational Mechanics, having authored 14 papers that have together received 309 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (9 papers), Advanced Neural Network Applications (7 papers), Prostate Cancer Diagnosis and Treatment (5 papers), Medical Imaging and Analysis (4 papers), Diabetic Foot Ulcer Assessment and Management (3 papers), 3D Shape Modeling and Analysis (2 papers), Lower Extremity Biomechanics and Pathologies (2 papers) and Hepatocellular Carcinoma Treatment and Prognosis (1 paper). The work is most often cited by research in Health Informatics (8 citations), Computer Vision and Pattern Recognition (94 citations), Radiology, Nuclear Medicine and Imaging (106 citations), Radiation (34 citations) and Hepatology (26 citations). Ruida Cheng has collaborated with scholars based in United States, Australia and Netherlands. Frequent co-authors include Evan McCreedy, Matthew McAuliffe, William Gandler, Barış Türkbey, Peter L. Choyke, Ronald M. Summers, Holger R. Roth, Le Lü, Ariela Sofer and Julia K. Locklin. Their work appears in journals such as Medical Physics, Magnetic Resonance in Medicine, Journal of Vascular and Interventional Radiology, Journal of Medical Imaging and Zenodo (CERN European Organization for Nuclear Research).
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.