Ling Yu

33 papers receiving 444 citations

Peers

Ling Yu
Comparison fields: 5 of 99
  • Obstetrics and Gynecology 101
  • Software 30
  • Cancer Research 78
  • Dermatology 39
  • Immunology 74
Replace Alyson Prorock with:
Alyson Prorock United States
A Alencar Brazil
Liwei Jia United States
Ying Chang China
Ruoyu Zhou China
Dimitrios Rafail Kalaitzopoulos Switzerland
Diane C. Saunders United States
Hongming Zhu China
И. С. Киселев Russia
Jianfeng Huang China
Ling Yu relative to Alyson Prorock United States Alyson Prorock's profile →
Citations per field
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Alyson Prorock · 1×
Citations per year

Countries citing papers authored by Ling Yu

Since Specialization
Citations

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

Fields of papers citing papers by Ling Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201257
2 202050
3 202249
4 200448
5 201437
6 202031
7 200723
8 202021
9 202320
10 201015
11 202210
12 20238
13 20158
14 20178
15 20237
16 20247
17 20156
18
[Trophoblast cells invaing the placenta bed and change of spiral arteries and microvessels in pre-eclampsia].
20086
19 20236
20 20146

About Ling Yu

Ling Yu is a scholar working on Obstetrics and Gynecology, Artificial Intelligence, Computer Networks and Communications, Pediatrics, Perinatology and Child Health and Information Systems, having authored 37 papers that have together received 457 indexed citations. Recurring topics across this work include Pregnancy and preeclampsia studies (11 papers), Reproductive System and Pregnancy (6 papers), Advanced Software Engineering Methodologies (6 papers), Birth, Development, and Health (5 papers), Software Engineering Research (4 papers), Software System Performance and Reliability (3 papers), MicroRNA in disease regulation (3 papers) and Service-Oriented Architecture and Web Services (2 papers). The work is most often cited by research in Obstetrics and Gynecology (101 citations), Software (30 citations), Cancer Research (78 citations), Dermatology (39 citations) and Immunology (74 citations). Ling Yu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Linfeng Li, Yiling Ding, Mei Peng, S.R. Schach, Jeff Offutt, Zvonimir S. Katušić, Livius V. d’Uscio, Hon-Chi Lee, Tong Lü and Tongrong He. Their work appears in journals such as American Journal of Reproductive Immunology, Computer, BMC Pregnancy and Childbirth, Journal of Assisted Reproduction and Genetics and International Immunopharmacology.

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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