Li Song

1.2k citations
69 papers · 827 indexed · h-index 17
Topics
Acute Myocardial Infarction Research (22 papers)Coronary Interventions and Diagnostics (18 papers)Cardiac Imaging and Diagnostics (15 papers)
Journals
Journal of Clinical OncologySHILAP Revista de lepidopterologíaBlood
Partner nations
ChinaUnited StatesMacao

In The Last Decade

Li Song

62 papers receiving 823 citations

Peers

Li Song
Comparison fields: 5 of 90
  • Molecular Biology 346
  • Cardiology and Cardiovascular Medicine 250
  • Surgery 172
  • Immunology 125
  • Physiology 113
Replace Takashi Nojiri with:
Takashi Nojiri Japan
Shi Peng China
Joshua DeLeon United States
Ting‐Ting Chang Taiwan
Jonathon Habersberger Australia
Hirotaka Yamamoto Japan
Zeinab Deris Zayeri Iran
Xiangming Wang China
Mengqi Gao China
Li Song relative to Takashi Nojiri Japan Takashi Nojiri's profile →
Citations per field
00.5×3.0×
Takashi Nojiri · 1×
Citations per year

Countries citing papers authored by Li Song

Since Specialization
Citations

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

Fields of papers citing papers by Li Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Li Song

This figure shows the co-authorship network connecting the top 25 collaborators of Li Song. A scholar is included among the top collaborators of Li Song 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 Li Song. Li Song 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
#WorkIndexed citations
1 0
2 0
3 0
4 0
5 19
6 1
7 1
8 3
9 3
10 4
11
Prognostic Value of Age-Adjusted D-Dimer Cutoff Thresholds in Patients with Acute Coronary Syndrome Treated by Percutaneous Coronary Intervention
2
12 9
13 5
14 5
15 9
16 5
17 20
18 5
19 36
20 20

About Li Song

Li Song is a scholar working on Cardiology and Cardiovascular Medicine, Cancer Research and Surgery, having authored 69 papers that have together received 827 indexed citations. Recurring topics across this work include Acute Myocardial Infarction Research (22 papers), Coronary Interventions and Diagnostics (18 papers) and Cardiac Imaging and Diagnostics (15 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (250 citations), Biological Psychiatry (18 citations) and Cancer Research (91 citations). Li Song has collaborated with scholars based in China, United States and Macao. Frequent co-authors include Hongbing Yan, Peng Zhou, Jiannan Li, Hanjun Zhao, Jinying Zhou, Zhaoxue Sheng, Runzhen Chen, Yu Ting Tan, Chen Liu and Chen Liu. Their work appears in journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.

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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