Shaoping Hu

925 citations
21 papers · 660 · 1 hit paper · h-index 10

Impact in

Papers in

Shaoping Hu

19 papers receiving 643 citations

Shaoping Hu's Hit Papers

Weakly Supervised Deep Learning for COVID-19 Infection Detection and Classification From CT Images 2020 · 300 citations
3000+2+4Years since publication100200300

Peers

Shaoping Hu
Comparison fields: 5 of 97
  • Health Informatics 55
  • Radiology, Nuclear Medicine and Imaging 300
  • Artificial Intelligence 186
  • Genetics 42
  • Pharmacology 32
Replace Jeong Hyun Lee with:
Jeong Hyun Lee South Korea
Zhen Zhou China
Wentian Guo China
Zirun Zhao United States
Qing Fu China
Veera Baladandayuthapani United States
Truong Nguyen Khanh Hung Vietnam
Enrique J. deAndrés‐Galiana Spain
Si-Cong Ma China
Liling Xu China
Shaoping Hu relative to Jeong Hyun Lee South Korea Jeong Hyun Lee's profile →
Citations per field
00.5×3.6×
Jeong Hyun Lee · 1×
Citations per year

Countries citing papers authored by Shaoping Hu

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Shaoping Hu Line = papers co-authored together Shaoping Hu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 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 →
2020300
2 201495
3 201575
4 201746
5 202029
6
TNF-α and IFN-γ synergistically inhibit the repairing ability of mesenchymal stem cells on mice colitis and colon cancer.
201918
7 202018
8 202017
9 202016
10 202010
11 20209
12 20207
13 20146
14 20215
15 20223
16 20213
17 20251
18 20221
19
Fast image template matching based on evolutionary algorithms
20041
20 20240

About Shaoping Hu

Shaoping Hu is a scholar working on Infectious Diseases, Neurology, Radiology, Nuclear Medicine and Imaging, Oncology and Cancer Research, having authored 21 papers that have together received 660 indexed citations. Recurring topics across this work include Long-Term Effects of COVID-19 (6 papers), COVID-19 Clinical Research Studies (6 papers), COVID-19 diagnosis using AI (4 papers), COVID-19 and healthcare impacts (3 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), MicroRNA in disease regulation (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Health Informatics (55 citations), Radiology, Nuclear Medicine and Imaging (300 citations), Artificial Intelligence (186 citations), Genetics (42 citations) and Pharmacology (32 citations). Shaoping Hu has collaborated with scholars based in China, United States and Germany. Frequent co-authors include J. Yuan, Tianhui Hu, Gang Song, Wei Zhong, Zhangming Niu, Yuan Gao, Hui Ye, Guang Yang, Wade Menpes-Smith and Li Lao. Their work appears in journals such as Oncotarget, Nature Communications, The American Journal of Chinese Medicine, Diagnostic and Interventional Imaging and Clinical Radiology.

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.

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