Qingjun Wang

1.1k total citations
54 papers, 765 citations indexed

About

Qingjun Wang is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Qingjun Wang has authored 54 papers receiving a total of 765 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Pulmonary and Respiratory Medicine, 11 papers in Radiology, Nuclear Medicine and Imaging and 10 papers in Molecular Biology. Recurrent topics in Qingjun Wang's work include Cardiac Imaging and Diagnostics (7 papers), Cerebrovascular and Carotid Artery Diseases (7 papers) and EEG and Brain-Computer Interfaces (4 papers). Qingjun Wang is often cited by papers focused on Cardiac Imaging and Diagnostics (7 papers), Cerebrovascular and Carotid Artery Diseases (7 papers) and EEG and Brain-Computer Interfaces (4 papers). Qingjun Wang collaborates with scholars based in China, United States and India. Qingjun Wang's co-authors include Rui Yang, Liang Zhao, Yan Zheng, Yugang Niu, Qingtang Su, Shifeng Zhao, Yun Tian, Jie Yin, Yuhong Jing and Xuewen Liu and has published in prestigious journals such as Journal of the American College of Cardiology, The Journal of Physiology and The FASEB Journal.

In The Last Decade

Qingjun Wang

51 papers receiving 742 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Qingjun Wang China 16 194 124 98 95 92 54 765
Lin Pan China 16 227 1.2× 81 0.7× 92 0.9× 53 0.6× 204 2.2× 97 920
Jianbing Zhu China 16 355 1.8× 63 0.5× 84 0.9× 75 0.8× 97 1.1× 59 847
Qinghua Peng China 15 335 1.7× 40 0.3× 50 0.5× 40 0.4× 143 1.6× 137 885
Lirong Wang China 17 144 0.7× 116 0.9× 87 0.9× 56 0.6× 111 1.2× 83 885
Do‐Young Kang South Korea 16 96 0.5× 49 0.4× 112 1.1× 146 1.5× 159 1.7× 47 693
Fang-Yuan Liu China 20 356 1.8× 71 0.6× 47 0.5× 54 0.6× 60 0.7× 63 1.1k
Jinliang Chen China 19 469 2.4× 65 0.5× 90 0.9× 144 1.5× 29 0.3× 65 1.1k
Lizhen Wu China 19 542 2.8× 131 1.1× 56 0.6× 60 0.6× 20 0.2× 71 1.3k
Tingting Ji China 15 108 0.6× 77 0.6× 31 0.3× 135 1.4× 29 0.3× 60 623

Countries citing papers authored by Qingjun Wang

Since Specialization
Citations

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

Fields of papers citing papers by Qingjun Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qingjun Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Qingjun Wang. A scholar is included among the top collaborators of Qingjun Wang 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 Qingjun Wang. Qingjun Wang 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
1.
Zhou, Shusen, et al.. (2024). Parallel Convolutional Contrastive Learning Method for Enzyme Function Prediction. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 21(6). 2604–2609.
2.
Zhou, Shusen, et al.. (2024). TSVM: Transfer Support Vector Machine for Predicting MPRA Validated Regulatory Variants. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 21(3). 472–479. 2 indexed citations
3.
Liu, Tong, et al.. (2023). Multi-modality Multi-attention Network for Ventricular Arrhythmia Classification. 331–336. 1 indexed citations
4.
Zhou, Shusen, et al.. (2023). CRMSNet : A deep learning model that uses convolution and residual multi‐head self‐attention block to predict RBPs for RNA sequence. Proteins Structure Function and Bioinformatics. 91(8). 1032–1041. 5 indexed citations
5.
Wang, Yaming, Qingjun Wang, Jing Han, et al.. (2023). The value of convolutional neural networks-based deep learning model in differential diagnosis of space-occupying brain diseases. Frontiers in Neurology. 14. 1107957–1107957. 2 indexed citations
6.
Han, Peng, Yuanchu She, Mengru Zhuang, et al.. (2022). Cbln1 regulates axon growth and guidance in multiple neural regions. PLoS Biology. 20(11). e3001853–e3001853. 6 indexed citations
7.
Wang, Qingjun, Liang Cui, Pansong Li, & Yuanyuan Wang. (2022). Somatic Mutation of FAT Family Genes Implicated Superior Prognosis in Patients With Stomach Adenocarcinoma. Frontiers in Medicine. 9. 873836–873836. 2 indexed citations
8.
Jia, Jing, et al.. (2021). Dynamic encoding of saccade sequences in primate frontal eye field. The Journal of Physiology. 599(22). 5061–5084. 4 indexed citations
9.
Chen, Yanhua, Qingjun Wang, Qizhen Liu, et al.. (2021). Design and engineering application of medical oxygen supply system in novel coronavirus pneumonia treatment hospital. Journal of Building Engineering. 44. 103170–103170. 4 indexed citations
10.
Zhang, Jun, Wenping Li, Yun Zhang, et al.. (2021). Diagnostic value of thyroid micronodules with high b-value diffusion weighted imaging: Comparative study with high-resolution ultrasound. European Journal of Radiology. 143. 109912–109912. 4 indexed citations
11.
Liu, Tao, Yun Tian, Shifeng Zhao, Xiaoying Huang, & Qingjun Wang. (2020). Residual Convolutional Neural Network for Cardiac Image Segmentation and Heart Disease Diagnosis. IEEE Access. 8. 82153–82161. 22 indexed citations
12.
Liu, Tao, Yun Tian, Shifeng Zhao, Xiaoying Huang, & Qingjun Wang. (2019). Automatic Whole Heart Segmentation Using a Two-Stage U-Net Framework and an Adaptive Threshold Window. IEEE Access. 7. 83628–83636. 33 indexed citations
13.
Tang, Yurong, et al.. (2018). Analysis of the Effect of 60Co-γ Irradiation Sterilization Technology on the Chemical Composition of Saffron Using UPLC and UPLC/Q-TOF-MS. Journal of Analytical Methods in Chemistry. 2018. 1–7. 11 indexed citations
14.
Yang, Rui, et al.. (2015). Edaravone injection ameliorates cognitive deficits in rat model of Alzheimer’s disease. Neurological Sciences. 36(11). 2067–2072. 24 indexed citations
15.
16.
Cai, Jianming, et al.. (2013). EFFECT OF LOW DOSE ROSUVASTATIN THERAPY ON REGRESSION OF CAROTID PLAQUE AND VASA VASORUMS IN CHINESE POPULATION: A PROSPECTs CLINICAL TRIAL BY MRI. Journal of the American College of Cardiology. 61(10). E938–E938. 1 indexed citations
17.
18.
Cai, Jianming, et al.. (2010). High-resolution MR study of the relationship between superficial calcification and the stability of carotid atherosclerotic plaque. International journal of cardiac imaging. 26(S1). 143–150. 25 indexed citations
19.
Wang, Qingjun. (2009). Contemplation of traditional sport going into media in China - taking "Wulin Assembly" on CCTV-5 for example.. journal of physical education. 16(4). 90–92.
20.
Zhao, Xihai, Hunter R. Underhill, Chun Yuan, et al.. (2009). Minimization of MR Contrast Weightings for the Comprehensive Evaluation of Carotid Atherosclerotic Disease. Investigative Radiology. 45(1). 36–41. 22 indexed citations

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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