Siyun Liu

809 total citations
51 papers, 557 citations indexed

About

Siyun Liu is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Surgery. According to data from OpenAlex, Siyun Liu has authored 51 papers receiving a total of 557 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Pulmonary and Respiratory Medicine and 7 papers in Surgery. Recurrent topics in Siyun Liu's work include Radiomics and Machine Learning in Medical Imaging (10 papers), Hepatocellular Carcinoma Treatment and Prognosis (4 papers) and Language, Metaphor, and Cognition (4 papers). Siyun Liu is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (10 papers), Hepatocellular Carcinoma Treatment and Prognosis (4 papers) and Language, Metaphor, and Cognition (4 papers). Siyun Liu collaborates with scholars based in China, United States and Spain. Siyun Liu's co-authors include Arthur G. Samuel, Bin Song, Xin Zhang, Fang Yuan, Jian Zhao, Jun Zhang, Zhenru Wu, Yujun Shi, Ying� Qin and Ning Wang and has published in prestigious journals such as PLoS ONE, Computers in Human Behavior and Magnetic Resonance in Medicine.

In The Last Decade

Siyun Liu

45 papers receiving 540 citations

Peers

Siyun Liu
Comparison fields: 5 of 99
  • Radiology, Nuclear Medicine and Imaging 184
  • Experimental and Cognitive Psychology 177
  • Cognitive Neuroscience 118
  • Oncology 76
  • Surgery 70
Replace Maki Sakamoto with:
Maki Sakamoto Japan
Kathleen Hutchinson United States
Roland Rydell Sweden
Kristina T. Johnson United States
Kosuke Nakajima Japan
Stephanie K. Patterson United States
Christine Chen United States
Yuan Zhao China
Alexander Y. Lin United States
Maki Sakamoto Japan View profile →
Citations per field, relative to Siyun Liu
Siyun Liu · 1×
Citations per year, relative to Siyun Liu
Siyun Liu · 1×

Countries citing papers authored by Siyun Liu

Since Specialization
Citations

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

Fields of papers citing papers by Siyun Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Siyun Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Siyun Liu. A scholar is included among the top collaborators of Siyun Liu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Siyun Liu. Siyun Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 3
2 0
3 0
4 0
5 2
6 7
7 2
8 8
9 2
10 3
11 10
12 16
13 12
14 38
15 41
16 41
17 16
18
Why Some Verbs are Harder to Learn than Others - A Micro-Level Analysis of Everyday Learning Contexts for Early Verb Learning.
3
19 4
20 1

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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