Liyi Chen

1.1k citations
69 papers · 646 · h-index 15

Impact in

Papers in

    • Infectious Diseases and Tuberculosis 7
    • Advanced Graph Neural Networks 5
    • Domain Adaptation and Few-Shot Learning 4
    • Topic Modeling 3

Liyi Chen

66 papers receiving 641 citations

Peers

Liyi Chen
Comparison fields: 5 of 100
  • Microbiology 33
  • Artificial Intelligence 175
  • Rheumatology 61
  • Computer Vision and Pattern Recognition 84
  • Cancer Research 46
Replace Dhammika Amaratunga with:
Dhammika Amaratunga United States
Mark Hughes Ireland
Zhaoguo Wang China
Burcu Bakır-Güngör Türkiye
Youxi Luo China
Xiaojian Shao Canada
Xiaolu Lu Australia
Muhammad Tahir Pakistan
Susanne Abraham Germany
Liyi Chen relative to Dhammika Amaratunga United States Dhammika Amaratunga's profile →
Citations per field
00.5×8.7×
Dhammika Amaratunga · 1×
Citations per year

Countries citing papers authored by Liyi Chen

Since Specialization
Citations

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

Fields of papers citing papers by Liyi Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202256
2 202053
3 202139
4 202334
5 201432
6 202226
7 202322
8 202221
9 201720
10 202018
11 202117
12 202316
13 202015
14 202114
15 202014
16 202312
17 202312
18 201911
19 202211
20 202311

About Liyi Chen

Liyi Chen is a scholar working on Surgery, Artificial Intelligence, Molecular Biology, Rheumatology and Computer Vision and Pattern Recognition, having authored 69 papers that have together received 646 indexed citations. Recurring topics across this work include Spondyloarthritis Studies and Treatments (8 papers), Infectious Diseases and Tuberculosis (7 papers), Multimodal Machine Learning Applications (5 papers), Advanced Graph Neural Networks (5 papers), Domain Adaptation and Few-Shot Learning (4 papers), Topic Modeling (3 papers), Spine and Intervertebral Disc Pathology (3 papers) and Recommender Systems and Techniques (3 papers). The work is most often cited by research in Microbiology (33 citations), Artificial Intelligence (175 citations), Rheumatology (61 citations), Computer Vision and Pattern Recognition (84 citations) and Cancer Research (46 citations). Liyi Chen has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Enhong Chen, Tong Xu, Zhi Li, Zhefeng Wang, Tuo Liang, Xinli Zhan, Jiarui Chen, Shengsheng Huang, Jie Jiang and Tianyou Chen. Their work appears in journals such as Medicine, BioMed Research International, Scientific Reports, Frontiers in Immunology and Nature and Science of Sleep.

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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