Shun Qi

820 citations
37 papers · 607 · h-index 16

Impact in

    • Functional Brain Connectivity Studies
    • Neuroscience and Music Perception
  • Neurology top 10%
    • Transcranial Magnetic Stimulation Studies
    • Traumatic Brain Injury and Neurovascular Disturbances

Papers in

Shun Qi

37 papers receiving 596 citations

Peers

Shun Qi
Comparison fields: 5 of 94
  • Cognitive Neuroscience 199
  • Neurology 67
  • Radiology, Nuclear Medicine and Imaging 151
  • Behavioral Neuroscience 22
  • Developmental Neuroscience 15
Replace Sunjay Shah with:
Sunjay Shah United States
Jerrel Rutlin United States
Qian Wu China
Jingming Hou China
Fabrizio Cocciolillo Italy
Fernando Fernandes Paiva Brazil
Mazal Cohen United Kingdom
Christopher Walker United States
Pernille Iversen Denmark
Shun Qi relative to Sunjay Shah United States Sunjay Shah's profile →
Citations per field
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Sunjay Shah · 1×
Citations per year

Countries citing papers authored by Shun Qi

Since Specialization
Citations

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

Fields of papers citing papers by Shun Qi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Shun Qi, 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 Shun Qi Line = papers co-authored together Shun Qi 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 201560
2 201243
3 201441
4 201741
5 201440
6 201738
7 201530
8 201327
9 202222
10 201422
11 201621
12 201221
13 202121
14 201618
15 202217
16 201516
17
Lymph node metastasis in patients with gastric cancer: a multi-modality, morphologic and functional imaging study.
201615
18 202214
19 201713
20 201611

About Shun Qi

Shun Qi is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging, Molecular Biology, Neurology and Epidemiology, having authored 37 papers that have together received 607 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (13 papers), Advanced Neuroimaging Techniques and Applications (9 papers), Transcranial Magnetic Stimulation Studies (5 papers), Advanced MRI Techniques and Applications (4 papers), MRI in cancer diagnosis (3 papers), Traumatic Brain Injury Research (3 papers), Mental Health Research Topics (3 papers) and Psychosomatic Disorders and Their Treatments (3 papers). The work is most often cited by research in Cognitive Neuroscience (199 citations), Neurology (67 citations), Radiology, Nuclear Medicine and Imaging (151 citations), Behavioral Neuroscience (22 citations) and Developmental Neuroscience (15 citations). Shun Qi has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Hong Yin, Long‐Biao Cui, Yi Huan, Huaning Wang, Lize Xiong, Feng Cao, Yuewen Hao, Ying Liu, Jing Yu and Lijun Sun. Their work appears in journals such as Medicine, Frontiers in Psychiatry, Frontiers in Neuroscience, Inflammation Research and Scientific Reports.

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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