Song Qing
- Biomedical Engineering
- Mechanical Engineering
- Artificial Intelligence top 10%
- Control and Systems Engineering
- Molecular Biology
- Topics
- Neural Networks and Applications (6 papers)Machine Learning and ELM (4 papers)Face and Expression Recognition (4 papers)
- Journals
- Journal of Applied Polymer ScienceBiomedicine & PharmacotherapyArtificial Intelligence Review
- Partner nations
- ChinaSingaporeUnited States
In The Last Decade
Song Qing
27 papers receiving 431 citations
Peers
Comparison fields: 5 of 92
- Biomedical Engineering 179
- Mechanical Engineering 151
- Artificial Intelligence 140
- Control and Systems Engineering 56
- Molecular Biology 55
Countries citing papers authored by Song Qing
This map shows the geographic impact of Song Qing'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 Qing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Song Qing more than expected).
Fields of papers citing papers by Song Qing
This network shows the impact of papers produced by Song Qing. 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 Qing. The network helps show where Song Qing may publish in the future.
Co-authorship network of co-authors of Song Qing
This figure shows the co-authorship network connecting the top 25 collaborators of Song Qing. A scholar is included among the top collaborators of Song Qing 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 Qing. Song Qing is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | 20 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | [Expression levels of miR-181c-3p and miR-5692b in esophageal cancer and their clinical significance]. | 4 |
| 8 | 3 | |
| 9 | 17 | |
| 10 | Survey on Network Security Situation Awareness | 0 |
| 11 | 47 | |
| 12 | 8 | |
| 13 | The verifying test of refueling system of the China experimental fast reactor | 3 |
| 14 | 188 | |
| 15 | 52 | |
| 16 | 2 | |
| 17 | 1 | |
| 18 | 13 | |
| 19 | Principle and engineering realization of Hall switch sensor | 0 |
| 20 | 44 |
About Song Qing
Song Qing is a scholar working on Artificial Intelligence, Control and Systems Engineering and Software, having authored 33 papers that have together received 453 indexed citations. Recurring topics across this work include Neural Networks and Applications (6 papers), Machine Learning and ELM (4 papers) and Face and Expression Recognition (4 papers). The work is most often cited by research in Artificial Intelligence (140 citations), Mechanical Engineering (151 citations) and Biomedical Engineering (179 citations). Song Qing has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Hong Yuan, Bolun Yang, Qing Shu, Gangli Zhu, Xulei Yang, Jizhong Xiao, Yeng Chai Soh, Xiangjun Li, Xinping Zhang and Pei‐Chann Chang. Their work appears in journals such as Journal of Applied Polymer Science, Biomedicine & Pharmacotherapy and Artificial Intelligence Review.
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.