Gailing Li

22 papers receiving 496 citations

Peers

Gailing Li
Comparison fields: 5 of 105
  • Statistics, Probability and Uncertainty 79
  • Cancer Research 95
  • Management Science and Operations Research 73
  • Control and Systems Engineering 90
  • Pharmaceutical Science 23
Replace Jiansheng Guo with:
Jiansheng Guo China
Nannan Ji China
Yuchang Mo China
Andrea Bommert Germany
Junwei Ou China
Zhichao Chen China
Li Guo China
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Citations per field
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Citations per year

Countries citing papers authored by Gailing Li

Since Specialization
Citations

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

Fields of papers citing papers by Gailing Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016107
2 201691
3 201878
4 200429
5 201829
6 202226
7 201926
8 201921
9 202415
10 201915
11 202114
12 202112
13 202210
14 20178
15 20196
16
Temporary Internal Iliac Artery Blockage versus Uterine Artery Embolization in Patients After Laparoscopic Pregnancy Tissue Removal Due to Cesarean Scar Pregnancy
20225
17 20165
18 20195
19 20223
20 20211

About Gailing Li

Gailing Li is a scholar working on Statistics, Probability and Uncertainty, Molecular Biology, Safety, Risk, Reliability and Quality, Artificial Intelligence and Cancer Research, having authored 24 papers that have together received 508 indexed citations. Recurring topics across this work include Risk and Safety Analysis (8 papers), Evaluation and Optimization Models (5 papers), Computational Drug Discovery Methods (2 papers), Software Reliability and Analysis Research (2 papers), Endometrial and Cervical Cancer Treatments (2 papers), Cancer-related molecular mechanisms research (2 papers), RNA Research and Splicing (2 papers) and Advanced Decision-Making Techniques (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (79 citations), Cancer Research (95 citations), Management Science and Operations Research (73 citations), Control and Systems Engineering (90 citations) and Pharmaceutical Science (23 citations). Gailing Li has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Changhua Hu, Leilei Chang, Zhiguo Zhou, Fujun Zhao, Zhijie Zhou, Zhijie Zhou, Liping Han, Liya Liu, Xiaoxiao Han and Mingbo Cai. Their work appears in journals such as Science China Information Sciences, Frontiers in Microbiology, Scientific Reports, International Journal of Approximate Reasoning and International Journal of Biological Macromolecules.

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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