Song Sheng

474 total citations
22 papers, 331 citations indexed

About

Song Sheng is a scholar working on Surgery, Pathology and Forensic Medicine and Epidemiology. According to data from OpenAlex, Song Sheng has authored 22 papers receiving a total of 331 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Surgery, 5 papers in Pathology and Forensic Medicine and 4 papers in Epidemiology. Recurrent topics in Song Sheng's work include Spine and Intervertebral Disc Pathology (3 papers), Spinal Fractures and Fixation Techniques (3 papers) and Computational Drug Discovery Methods (2 papers). Song Sheng is often cited by papers focused on Spine and Intervertebral Disc Pathology (3 papers), Spinal Fractures and Fixation Techniques (3 papers) and Computational Drug Discovery Methods (2 papers). Song Sheng collaborates with scholars based in China, Canada and United States. Song Sheng's co-authors include Jeri‐Anne Lyons, Nhial T. Tutlam, Kathryn Trinkaus, Anne H. Cross, Laura Piccio, Robert T. Naismith, Becky Parks, Fengqin Xu, Ye Huang and Yanhong Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Neurology and Frontiers in Immunology.

In The Last Decade

Song Sheng

22 papers receiving 325 citations

Peers

Song Sheng
Comparison fields: 5 of 86
  • Pathology and Forensic Medicine 163
  • Immunology 98
  • Molecular Biology 52
  • Neurology 48
  • Surgery 46
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Citations per field, relative to Song Sheng
Song Sheng · 1×
Citations per year, relative to Song Sheng
Song Sheng · 1×

Countries citing papers authored by Song Sheng

Since Specialization
Citations

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

Fields of papers citing papers by Song Sheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Song Sheng

This figure shows the co-authorship network connecting the top 25 collaborators of Song Sheng. A scholar is included among the top collaborators of Song Sheng 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 Song Sheng. Song Sheng 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 8
3 2
4 41
5 3
6 2
7 2
8 2
9 21
10 9
11 10
12 6
13 17
14 3
15
[A COMPARATIVE STUDY ON TREATMENT OF MID-THORACIC OSTEOPOROTIC VERTEBRAL COMPRESSION FRACTURE USING PERCUTANEOUS KYPHOPLASTY WITH UNILATERAL AND BILATERAL APPROACHES].
4
16 11
17 9
18
[EFFECTIVENESS COMPARISON OF USING BONE TRANSPORT AND BONE SHORTENING-LENGTHENING FOR TIBIAL BONE AND SOFT TISSUE DEFECTS].
3
19 169
20
GENETIC OPTIMIZATION OF HOT FILAMENT PARAMETERS IN HFCVD SYSTEM
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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