Xiaoping Yin
Impact in
- Infectious Diseases top 5%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
- Neurology top 10%
- Long-Term Effects of COVID-19
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 10
- COVID-19 diagnosis using AI 4
- Radiation Dose and Imaging 3
-
- Cerebrovascular and Carotid Artery Diseases 3
Xiaoping Yin
26 papers receiving 638 citations
Hit Papers
Peers
Comparison fields: 5 of 87
- Infectious Diseases 292
- Neurology 162
- Radiology, Nuclear Medicine and Imaging 183
- Critical Care and Intensive Care Medicine 41
- Biological Psychiatry 11
Countries citing papers authored by Xiaoping Yin
This map shows the geographic impact of Xiaoping Yin'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 Xiaoping Yin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoping Yin more than expected).
Fields of papers citing papers by Xiaoping Yin
This network shows the impact of papers produced by Xiaoping Yin. 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 Xiaoping Yin. The network helps show where Xiaoping Yin may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiaoping Yin, 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 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 1 | |
| 8 | 2023 | 4 | |
| 9 | Clinical and computed tomographic imaging features of novel coronavirus pneumonia caused by SARS-CoV-2 Hit paper breakdown → | 2020 | 372 |
| 10 | 2020 | 11 | |
| 11 | 2020 | 12 | |
| 12 | 2020 | 12 | |
| 13 | 2019 | 31 | |
| 14 | 2019 | 6 | |
| 15 | 2018 | 1 | |
| 16 | 2018 | 2 | |
| 17 | 2018 | 11 | |
| 18 | 2017 | 9 | |
| 19 | 2016 | 93 | |
| 20 | Tick fauna and monitoring of tick host animals at Alataw Pass. | 2010 | 2 |
About Xiaoping Yin
Xiaoping Yin is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Infectious Diseases, Internal Medicine and Neurology, having authored 32 papers that have together received 656 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (10 papers), Advanced X-ray and CT Imaging (5 papers), AI in cancer detection (4 papers), COVID-19 Clinical Research Studies (4 papers), COVID-19 diagnosis using AI (4 papers), Radiation Dose and Imaging (3 papers), Cerebrovascular and Carotid Artery Diseases (3 papers) and Neonatal and fetal brain pathology (2 papers). The work is most often cited by research in Infectious Diseases (292 citations), Neurology (162 citations), Radiology, Nuclear Medicine and Imaging (183 citations), Critical Care and Intensive Care Medicine (41 citations) and Biological Psychiatry (11 citations). Xiaoping Yin has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Bu‐Lang Gao, Li Dong, Jianzeng Zhang, Jinghui Dong, Xi Ma, Weimin An, Yuhuan Xu, Hongjie Zhang, Lijun Xu and Bo Wei. Their work appears in journals such as European Journal of Radiology, Scientific Reports, Journal of Biomechanics, Behavioural Brain Research and Frontiers in Bioengineering and Biotechnology.
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.