Bibo Shi
Impact in
- Health Informatics top 10%
-
- Brain Tumor Detection and Classification
Papers in
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- Radiomics and Machine Learning in Medical Imaging 6
- Medical Imaging Techniques and Applications 3
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- Face and Expression Recognition 3
- Medical Image Segmentation Techniques 3
- Human Pose and Action Recognition 3
- Co-authors
- Jundong Liu (6 shared papers)Yani Chen (3 shared papers)Pin Zhang (4 shared papers)Joseph Y. Lo (7 shared papers)Charles D. Smith (3 shared papers)Maciej A. Mazurowski (6 shared papers)Carlo C. Maley (6 shared papers)Jeffrey R. Marks (6 shared papers)
- Journals
- Pattern Recognition (1 paper)Annals of Oncology (1 paper)Academic Radiology (1 paper)Journal of the American College of Radiology (1 paper)PLoS ONE (1 paper)
- Partner nations
- United StatesChinaSwitzerland
In The Last Decade
Bibo Shi
24 papers receiving 365 citations
Peers
Comparison fields: 5 of 74
- Health Informatics 19
- Neurology 58
- Radiology, Nuclear Medicine and Imaging 159
- Artificial Intelligence 151
- Computer Vision and Pattern Recognition 75
Countries citing papers authored by Bibo Shi
This map shows the geographic impact of Bibo Shi'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 Bibo Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bibo Shi more than expected).
Fields of papers citing papers by Bibo Shi
This network shows the impact of papers produced by Bibo Shi. 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 Bibo Shi. The network helps show where Bibo Shi may publish in the future.
Co-authors
The 25 scholars most cited alongside Bibo Shi, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 70 | |
| 2 | 2018 | 63 | |
| 3 | 2018 | 44 | |
| 4 | 2020 | 35 | |
| 5 | 2017 | 32 | |
| 6 | 2020 | 24 | |
| 7 | 2020 | 19 | |
| 8 | 2018 | 19 | |
| 9 | 2017 | 17 | |
| 10 | 2014 | 13 | |
| 11 | 2014 | 7 | |
| 12 | 2015 | 7 | |
| 13 | 2016 | 5 | |
| 14 | 2018 | 4 | |
| 15 | 2014 | 3 | |
| 16 | 2017 | 3 | |
| 17 | 2014 | 2 | |
| 18 | 2021 | 2 | |
| 19 | 2018 | 1 | |
| 20 | 2017 | 1 |
About Bibo Shi
Bibo Shi is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Artificial Intelligence, Pulmonary and Respiratory Medicine and Biomedical Engineering, having authored 25 papers that have together received 375 indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Lung Cancer Diagnosis and Treatment (4 papers), Face and Expression Recognition (3 papers), Medical Imaging Techniques and Applications (3 papers), Prostate Cancer Diagnosis and Treatment (3 papers), Medical Image Segmentation Techniques (3 papers) and Human Pose and Action Recognition (3 papers). The work is most often cited by research in Health Informatics (19 citations), Neurology (58 citations), Radiology, Nuclear Medicine and Imaging (159 citations), Artificial Intelligence (151 citations) and Computer Vision and Pattern Recognition (75 citations). Bibo Shi has collaborated with scholars based in United States, China and Switzerland. Frequent co-authors include Jundong Liu, Yani Chen, Pin Zhang, Joseph Y. Lo, Charles D. Smith, Maciej A. Mazurowski, Carlo C. Maley, Jeffrey R. Marks, Lorraine King and Lars J. Grimm. Their work appears in journals such as Pattern Recognition, Annals of Oncology, Academic Radiology, Journal of the American College of Radiology and PLoS ONE.
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.