Shaoping Hu
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
Papers in ⓘ
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- COVID-19 Clinical Research Studies 8
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- Long-Term Effects of COVID-19 7
- Co-authors
- Tianhui Hu (4 shared papers)J. Yuan (4 shared papers)Gang Song (4 shared papers)Wei Zhong (3 shared papers)Evandro Fei Fang (1 shared paper)Minhao Wang (1 shared paper)Yuan Gao (1 shared paper)Hui Ye (1 shared paper)
- Journals
- Oncotarget (2 papers)iScience (1 paper)Current Neuropharmacology (1 paper)Clinical Radiology (1 paper)Therapeutic Advances in Chronic Disease (1 paper)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Shaoping Hu
19 papers receiving 613 citations
Hit Papers
Peers
Comparison fields: 5 of 95
- Health Informatics 66
- Radiology, Nuclear Medicine and Imaging 288
- Artificial Intelligence 178
- Pharmacology 44
- Genetics 46
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 22 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 | 276 |
| 2 | 2014 | 94 | |
| 3 | 2015 | 73 | |
| 4 | 2017 | 45 | |
| 5 | 2020 | 28 | |
| 6 | 2020 | 18 | |
| 7 | TNF-α and IFN-γ synergistically inhibit the repairing ability of mesenchymal stem cells on mice colitis and colon cancer. | 2019 | 18 |
| 8 | 2020 | 16 | |
| 9 | 2020 | 14 | |
| 10 | 2020 | 10 | |
| 11 | 2020 | 9 | |
| 12 | 2020 | 7 | |
| 13 | 2014 | 6 | |
| 14 | 2021 | 5 | |
| 15 | 2021 | 3 | |
| 16 | 2022 | 3 | |
| 17 | 2025 | 1 | |
| 18 | 2022 | 1 | |
| 19 | Fast image template matching based on evolutionary algorithms | 2004 | 1 |
| 20 | 2024 | 0 |
About Shaoping Hu
Shaoping Hu is a scholar working on Infectious Diseases, Neurology, Radiology, Nuclear Medicine and Imaging, Oncology and Immunology, having authored 22 papers that have together received 628 indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (8 papers), Long-Term Effects of COVID-19 (7 papers), COVID-19 diagnosis using AI (5 papers), COVID-19 and healthcare impacts (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), MicroRNA in disease regulation (2 papers), Cancer-related molecular mechanisms research (2 papers) and Cholangiocarcinoma and Gallbladder Cancer Studies (2 papers). The work is most often cited by research in Health Informatics (66 citations), Radiology, Nuclear Medicine and Imaging (288 citations), Artificial Intelligence (178 citations), Pharmacology (44 citations) and Genetics (46 citations). Shaoping Hu has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Tianhui Hu, J. Yuan, Gang Song, Wei Zhong, Evandro Fei Fang, Minhao Wang, Yuan Gao, Hui Ye, Yinghui Jiang and Jun Xia. Their work appears in journals such as Oncotarget, iScience, Current Neuropharmacology, Clinical Radiology and Therapeutic Advances in Chronic Disease.
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.