Feng Shi
- Health Informatics top 0.2%
-
- Radiomics and Machine Learning in Medical Imaging 61
- Advanced Neuroimaging Techniques and Applications 54
- Advanced MRI Techniques and Applications 36
- Medical Imaging Techniques and Applications 22
- COVID-19 diagnosis using AI 21
- Cognitive Neuroscience top 0.5%
- Functional Brain Connectivity Studies 58
- Neurology top 1%
-
- Neonatal and fetal brain pathology 38
-
- Medical Image Segmentation Techniques 57
- Partner nations
- ChinaUnited StatesSouth Korea
In The Last Decade
Feng Shi
392 papers receiving 11.8k citations
Hit Papers
Peers
Comparison fields: 5 of 220
- Health Informatics 276
- Radiology, Nuclear Medicine and Imaging 4.2k
- Cognitive Neuroscience 3.4k
- Neurology 817
- Pediatrics, Perinatology and Child Health 1.8k
Countries citing papers authored by Feng Shi
This map shows the geographic impact of Feng 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 Feng Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Feng Shi more than expected).
Fields of papers citing papers by Feng Shi
This network shows the impact of papers produced by Feng 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 Feng Shi. The network helps show where Feng Shi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Feng 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
| # | Work | ||
|---|---|---|---|
| 1 | 2026 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 2 | |
| 4 | 2025 | 0 | |
| 5 | 2024 | 9 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 11 | |
| 8 | 2024 | 1 | |
| 9 | 2024 | 7 | |
| 10 | 2023 | 22 | |
| 11 | 2023 | 67 | |
| 12 | 2023 | 16 | |
| 13 | 2023 | 16 | |
| 14 | 2023 | 2 | |
| 15 | 2023 | 11 | |
| 16 | 2023 | 1 | |
| 17 | 2022 | 13 | |
| 18 | 2020 | 12 | |
| 19 | 2014 | 45 | |
| 20 | 2013 | 10 |
About Feng Shi
Feng Shi is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Neurology and Pediatrics, Perinatology and Child Health, having authored 448 papers that have together received 12.0k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (61 papers), Functional Brain Connectivity Studies (58 papers), Medical Image Segmentation Techniques (57 papers), Advanced Neuroimaging Techniques and Applications (54 papers), Neonatal and fetal brain pathology (38 papers), Advanced MRI Techniques and Applications (36 papers), Medical Imaging Techniques and Applications (22 papers) and COVID-19 diagnosis using AI (21 papers). The work is most often cited by research in Health Informatics (276 citations), Radiology, Nuclear Medicine and Imaging (4.2k citations), Cognitive Neuroscience (3.4k citations), Neurology (817 citations) and Pediatrics, Perinatology and Child Health (1.8k citations). Feng Shi has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Dinggang Shen, Weili Lin, John H. Gilmore, Li Wang, Gang Li, Pew‐Thian Yap, Guorong Wu, Yaozong Gao, Tianzi Jiang and Chunshui Yu. Their work appears in journals such as NeuroImage, PLoS ONE, IEEE Transactions on Medical Imaging, Human Brain Mapping and Medical Image Analysis.
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.