Shaoping Hu
Impact in
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- COVID-19 diagnosis using AI
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- Mesenchymal stem cell research
- Inflammatory Bowel Disease
Papers in
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- COVID-19 Clinical Research Studies 7
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- COVID-19 diagnosis using AI 2
- Co-authors
- Gang Song (4 shared papers)Tianhui Hu (4 shared papers)Jiahui Yuan (4 shared papers)Guang Zhong Yang (1 shared paper)Xianglu Xiao (1 shared paper)Yinghui Jiang (1 shared paper)Zhangming Niu (1 shared paper)Jun Xia (1 shared paper)
- Journals
- Nature Communications (2 papers)Oncotarget (2 papers)Current Neuropharmacology (1 paper)Journal of Alzheimer s Disease (1 paper)Frontiers in Medicine (1 paper)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Shaoping Hu
22 papers receiving 667 citations
Shaoping Hu's Hit Papers
Peers
Comparison fields: 5 of 71
- Radiology, Nuclear Medicine and Imaging 273
- Genetics 49
- Health Informatics 10
- Neurology 46
- Infectious Diseases 52
Countries citing papers authored by Shaoping Hu
This map shows the geographic impact of Shaoping Hu'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 Shaoping Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaoping Hu more than expected).
Fields of papers citing papers by Shaoping Hu
This network shows the impact of papers produced by Shaoping Hu. 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 Shaoping Hu. The network helps show where Shaoping Hu may publish in the future.
Co-authors
The 25 scholars most cited alongside Shaoping Hu, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Weakly Supervised Deep Learning for COVID-19 Infection Detection and Classification From CT Images Hit paper breakdown → | 2020 | 306 |
| 2 | 2014 | 95 | |
| 3 | 2015 | 78 | |
| 4 | 2017 | 47 | |
| 5 | 2020 | 29 | |
| 6 | 2020 | 20 | |
| 7 | 2020 | 20 | |
| 8 | TNF-α and IFN-γ synergistically inhibit the repairing ability of mesenchymal stem cells on mice colitis and colon cancer. | 2019 | 18 |
| 9 | 2020 | 16 | |
| 10 | 2020 | 10 | |
| 11 | 2020 | 10 | |
| 12 | 2014 | 7 | |
| 13 | 2020 | 7 | |
| 14 | 2021 | 5 | |
| 15 | 2022 | 5 | |
| 16 | 2024 | 5 | |
| 17 | 2020 | 4 | |
| 18 | 2021 | 3 | |
| 19 | 2025 | 2 | |
| 20 | Fast image template matching based on evolutionary algorithms | 2004 | 1 |
About Shaoping Hu
Shaoping Hu is a scholar working on Infectious Diseases, Radiology, Nuclear Medicine and Imaging, Neurology, Medical Laboratory Technology and Oncology, having authored 23 papers that have together received 690 indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (7 papers), Long-Term Effects of COVID-19 (3 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (2 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (2 papers), COVID-19 diagnosis using AI (2 papers), Phytochemistry and Biological Activities (1 paper), Microbial infections and disease research (1 paper) and Medicinal plant effects and applications (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (273 citations), Genetics (49 citations), Health Informatics (10 citations), Neurology (46 citations) and Infectious Diseases (52 citations). Shaoping Hu has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Gang Song, Tianhui Hu, Jiahui Yuan, Guang Zhong Yang, Xianglu Xiao, Yinghui Jiang, Zhangming Niu, Jun Xia, Yuan Gao and Evandro Fei Fang. Their work appears in journals such as Nature Communications, Oncotarget, Current Neuropharmacology, Journal of Alzheimer s Disease and Frontiers in Medicine.
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.