Song Dong

863 total citations · 1 hit paper
34 papers, 466 citations indexed

About

Song Dong is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Molecular Biology. According to data from OpenAlex, Song Dong has authored 34 papers receiving a total of 466 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Pulmonary and Respiratory Medicine, 11 papers in Oncology and 7 papers in Molecular Biology. Recurrent topics in Song Dong's work include Lung Cancer Diagnosis and Treatment (12 papers), Lung Cancer Treatments and Mutations (10 papers) and Radiomics and Machine Learning in Medical Imaging (5 papers). Song Dong is often cited by papers focused on Lung Cancer Diagnosis and Treatment (12 papers), Lung Cancer Treatments and Mutations (10 papers) and Radiomics and Machine Learning in Medical Imaging (5 papers). Song Dong collaborates with scholars based in China, India and Canada. Song Dong's co-authors include Yi‐Long Wu, Wen‐Zhao Zhong, Xue‐Ning Yang, Qiang Nie, Zhihong Chen, Qing Zhou, Xu‐Chao Zhang, Hong‐Hong Yan, Xue‐Wu Wei and Fen Wang and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Cancer Research.

In The Last Decade

Song Dong

33 papers receiving 464 citations

Hit Papers

Single-cell transcriptome analysis revealed a suppressive... 2022 2026 2023 2024 2022 40 80 120

Peers

Song Dong
Comparison fields: 5 of 66
  • Pulmonary and Respiratory Medicine 277
  • Oncology 250
  • Molecular Biology 115
  • Cancer Research 107
  • Immunology 48
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Citations per field, relative to Song Dong
Song Dong · 1×
Citations per year, relative to Song Dong
Song Dong · 1×

Countries citing papers authored by Song Dong

Since Specialization
Citations

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

Fields of papers citing papers by Song Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Song Dong

This figure shows the co-authorship network connecting the top 25 collaborators of Song Dong. A scholar is included among the top collaborators of Song Dong 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 Dong. Song Dong 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 1
2 2
3 3
4 21
5
Single-cell transcriptome analysis revealed a suppressive tumor immune microenvironment in EGFR mutant lung adenocarcinoma breakdown →
120
6 7
7 13
8 4
9 8
10
Circular RNA hsa_circ_0068033 Acts as a Diagnostic Biomarker and Suppresses the Progression of Breast Cancer Through Sponging miR-659
1
11 1
12 66
13
[Renal mucinous tubular and spindle cell carcinoma combined with multiple bone metastasis: a case report and literature review].
1
14 2
15 1
16 0
17 1
18 16
19 14
20 19

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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