Jun Wei
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- COVID-19 diagnosis using AI
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- Digital Radiography and Breast Imaging
- Lung Cancer Diagnosis and Treatment
Papers in
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- Radiomics and Machine Learning in Medical Imaging 39
- Medical Imaging Techniques and Applications 34
- Cardiac Imaging and Diagnostics 12
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- Digital Radiography and Breast Imaging 55
- Lung Cancer Diagnosis and Treatment 11
- Co-authors
- Heang‐Ping Chan (112 shared papers)Lubomir M. Hadjiiski (111 shared papers)Chuan Zhou (85 shared papers)Berkman Sahiner (56 shared papers)Mark A. Helvie (44 shared papers)Jun Ge (24 shared papers)Yao Lu (36 shared papers)Ravi K. Samala (19 shared papers)
- Journals
- Medical Physics (38 papers)Physics in Medicine and Biology (9 papers)Radiology (4 papers)Frontiers in Oncology (3 papers)Academic Radiology (2 papers)
- Partner nations
- United StatesChinaBulgaria
In The Last Decade
Jun Wei
153 papers receiving 3.1k citations
Peers
Comparison fields: 5 of 131
- Radiology, Nuclear Medicine and Imaging 1.6k
- Pulmonary and Respiratory Medicine 1.3k
- Artificial Intelligence 1.3k
- Health Informatics 48
- Computer Vision and Pattern Recognition 524
Countries citing papers authored by Jun Wei
This map shows the geographic impact of Jun Wei'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 Jun Wei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Wei more than expected).
Fields of papers citing papers by Jun Wei
This network shows the impact of papers produced by Jun Wei. 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 Jun Wei. The network helps show where Jun Wei may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Wei, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 160 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 242 | |
| 2 | 2006 | 224 | |
| 3 | 2003 | 148 | |
| 4 | 2005 | 107 | |
| 5 | 2017 | 101 | |
| 6 | 2004 | 100 | |
| 7 | 2007 | 95 | |
| 8 | 2005 | 89 | |
| 9 | 2020 | 80 | |
| 10 | 2011 | 73 | |
| 11 | 2007 | 72 | |
| 12 | 2006 | 71 | |
| 13 | 2008 | 70 | |
| 14 | 2005 | 66 | |
| 15 | 2019 | 58 | |
| 16 | 2017 | 53 | |
| 17 | 2011 | 50 | |
| 18 | 2014 | 48 | |
| 19 | 2011 | 46 | |
| 20 | 2007 | 46 |
About Jun Wei
Jun Wei is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Artificial Intelligence, Internal Medicine and Oncology, having authored 160 papers that have together received 3.2k indexed citations. Recurring topics across this work include AI in cancer detection (59 papers), Digital Radiography and Breast Imaging (55 papers), Radiomics and Machine Learning in Medical Imaging (39 papers), Medical Imaging Techniques and Applications (34 papers), Colorectal Cancer Screening and Detection (16 papers), Cardiac Imaging and Diagnostics (12 papers), Advanced X-ray and CT Imaging (11 papers) and Lung Cancer Diagnosis and Treatment (11 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.6k citations), Pulmonary and Respiratory Medicine (1.3k citations), Artificial Intelligence (1.3k citations), Health Informatics (48 citations) and Computer Vision and Pattern Recognition (524 citations). Jun Wei has collaborated with scholars based in United States, China and Bulgaria. Frequent co-authors include Heang‐Ping Chan, Lubomir M. Hadjiiski, Chuan Zhou, Berkman Sahiner, Mark A. Helvie, Jun Ge, Yao Lu, Ravi K. Samala, Marilyn A. Roubidoux and Yiheng Zhang. Their work appears in journals such as Medical Physics, Physics in Medicine and Biology, Radiology, Frontiers in Oncology and Academic Radiology.
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.