Yan Qiang

899 total citations · 1 hit paper
11 papers, 600 citations indexed

About

Yan Qiang is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Yan Qiang has authored 11 papers receiving a total of 600 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 4 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Yan Qiang's work include Privacy-Preserving Technologies in Data (5 papers), Cryptography and Data Security (4 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Yan Qiang is often cited by papers focused on Privacy-Preserving Technologies in Data (5 papers), Cryptography and Data Security (4 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Yan Qiang collaborates with scholars based in China, United States and Singapore. Yan Qiang's co-authors include Nan Liu, Chuan Chen, Zibin Zheng, Huawei Huang, Yuzheng Li, Xiaolong Zhang, Jiangtian Nie, Xuandi Li, Dusit Niyato and Yi Liu and has published in prestigious journals such as PLoS ONE, Information Sciences and Applied Sciences.

In The Last Decade

Yan Qiang

10 papers receiving 588 citations

Hit Papers

A Blockchain-Based Decentralized Federated Learning Frame... 2020 2026 2022 2024 2020 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A Blockchain-Based Decentralized Federated Learning Framework with Committee Consensus
    2020 416 citations Yuzheng Li, Chuan Chen et al. IEEE Network profile →

Peers

Yan Qiang
Hyesung Kim South Korea
Yiqun Diao Singapore
Mohammed Kaosar Australia
Lichuan Ma China
Y. Ding China
Moming Duan China
Ahmad Al‐Ahmad Kuwait
Ruxia Sun China
Briland Hitaj United States
Hyesung Kim South Korea
Yan Qiang
Citations per year, relative to Yan Qiang Yan Qiang (= 1×) peers Hyesung Kim

Countries citing papers authored by Yan Qiang

Since Specialization
Citations

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

Fields of papers citing papers by Yan Qiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yan Qiang

This figure shows the co-authorship network connecting the top 25 collaborators of Yan Qiang. A scholar is included among the top collaborators of Yan Qiang 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 Yan Qiang. Yan Qiang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
1.
Kang, Jiawen, Xuandi Li, Jiangtian Nie, et al.. (2022). Communication-Efficient and Cross-Chain Empowered Federated Learning for Artificial Intelligence of Things. IEEE Transactions on Network Science and Engineering. 9(5). 2966–2977. 73 indexed citations
2.
Zheng, Shuyuan, Yang Cao, Masatoshi Yoshikawa, Huizhong Li, & Yan Qiang. (2022). FL-Market: Trading Private Models in Federated Learning. 2022 IEEE International Conference on Big Data (Big Data). 1525–1534. 14 indexed citations
3.
Li, Yuzheng, Chuan Chen, Nan Liu, et al.. (2020). A Blockchain-Based Decentralized Federated Learning Framework with Committee Consensus. IEEE Network. 35(1). 234–241. 416 indexed citations breakdown →
4.
Li, Xiaoli, Nan Liu, Chuan Chen, et al.. (2020). Communication-Efficient Collaborative Learning of Geo-Distributed JointCloud from Heterogeneous Datasets. 7 indexed citations
5.
Qiang, Yan, et al.. (2019). Using BERT for Checking the Polarity of Movie Reviews. International Journal of Computer Applications. 177(21). 37–41. 10 indexed citations
6.
Qiang, Yan, et al.. (2018). An Automated Segmentation Method for Lung Parenchyma Image Sequences Based on Fractal Geometry and Convex Hull Algorithm. Applied Sciences. 8(5). 832–832. 16 indexed citations
7.
8.
Qiang, Yan, Lei Ge, Xin Zhao, Xiaolong Zhang, & Xiaoxian Tang. (2017). Pulmonary nodule diagnosis using dual‐modal supervised autoencoder based on extreme learning machine. Expert Systems. 34(6). 12 indexed citations
9.
Zhang, Xiaolong, et al.. (2017). Pulmonary parenchyma segmentation in thin CT image sequences with spectral clustering and geodesic active contour model based on similarity. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10420. 104202G–104202G. 4 indexed citations
10.
Lai, Junzuo, Yingjiu Li, Robert H. Deng, et al.. (2014). Towards semantically secure outsourcing of association rule mining on categorical data. Information Sciences. 267. 267–286. 20 indexed citations
11.
Qiang, Yan. (2010). Application of Workload Adaptation Technology on Power Marketing Management System.

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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