Xiaoping Li

504 citations
30 papers · 344 · h-index 9

Impact in

Papers in

Xiaoping Li

24 papers receiving 332 citations

Peers

Xiaoping Li
Comparison fields: 5 of 105
  • Computer Vision and Pattern Recognition 101
  • Obstetrics and Gynecology 36
  • Reproductive Medicine 31
  • Cancer Research 52
  • Media Technology 17
Replace Rashmi Mukherjee with:
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Ziqi Zhou China
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Fangcen Liu China
Seppo Virtanen Finland
Cuncong Zhong United States
Sanghamitra Satpathi India
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Xiaoping Li relative to Rashmi Mukherjee India Rashmi Mukherjee's profile →
Citations per field
00.5×1.5×2.1×
Rashmi Mukherjee · 1×
Citations per year

Countries citing papers authored by Xiaoping Li

Since Specialization
Citations

This map shows the geographic impact of Xiaoping Li'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 Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoping Li more than expected).

Fields of papers citing papers by Xiaoping Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaoping Li. 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 Li. The network helps show where Xiaoping Li may publish in the future.

Co-authors

The 25 scholars most cited alongside Xiaoping Li, 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 Xiaoping Li Line = papers co-authored together Xiaoping Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020128
2 202341
3 202238
4 202223
5 201418
6 202114
7 200813
8 202212
9 20219
10 20208
11 20167
12 20156
13 20214
14 20194
15 20243
16 20233
17 20253
18 20252
19
[Treatment of equinovarus caused by cerebral palsy with neurotomy of muscular branch of tibial nerve].
20092
20 20251

About Xiaoping Li

Xiaoping Li is a scholar working on Molecular Biology, Surgery, Cardiology and Cardiovascular Medicine, Cancer Research and Epidemiology, having authored 30 papers that have together received 344 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (4 papers), Endometrial and Cervical Cancer Treatments (3 papers), Plant Virus Research Studies (2 papers), RNA Interference and Gene Delivery (2 papers), Biosensors and Analytical Detection (2 papers), Herpesvirus Infections and Treatments (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 Computer Vision and Pattern Recognition (101 citations), Obstetrics and Gynecology (36 citations), Reproductive Medicine (31 citations), Cancer Research (52 citations) and Media Technology (17 citations). Xiaoping Li has collaborated with scholars based in China, Macao and United States. Frequent co-authors include Xinggang Wang, Zhi Chen, Jianliu Wang, Xinling Zhang, Ying Xiao, Tian Zhong, Chengliang Yin, Ling Wang, Yu Xi and Heng Cui. Their work appears in journals such as Frontiers in Bioengineering and Biotechnology, Vaccines, Image and Vision Computing, Medicine and Microbial 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.

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