Mingquan Ye

820 total citations · 1 hit paper
39 papers, 527 citations indexed

About

Mingquan Ye is a scholar working on Molecular Biology, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mingquan Ye has authored 39 papers receiving a total of 527 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 12 papers in Artificial Intelligence and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Mingquan Ye's work include Medical Image Segmentation Techniques (6 papers), Rough Sets and Fuzzy Logic (6 papers) and Gene expression and cancer classification (5 papers). Mingquan Ye is often cited by papers focused on Medical Image Segmentation Techniques (6 papers), Rough Sets and Fuzzy Logic (6 papers) and Gene expression and cancer classification (5 papers). Mingquan Ye collaborates with scholars based in China and United States. Mingquan Ye's co-authors include Lingyun Gao, Xuegang Hu, Xindong Wu, Donghui Hu, Xiaocen Liu, Peipei Wang, Hui Yang, Qingqing Li, Kun Lv and Maosheng Wang and has published in prestigious journals such as Journal of Neurophysiology, Molecules and Frontiers in Microbiology.

In The Last Decade

Mingquan Ye

34 papers receiving 513 citations

Hit Papers

align trajectories

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.

Changing trends in the global burden of mental disorders from 1990 to 2019 and predicted levels in 25 years

2023 66 citations Lu Wang, Hui Yuan et al. Epidemiology and Psychiatric Sciences profile →

Peers

Mingquan Ye

AI

MB

CVPR

RNMI

CTM

Hany Alashwal United Arab Emirates

Aristidis G. Vrahatis Greece

Blaise Hanczar France

Zerrin Işık Türkiye

Janani Venugopalan United States

Yang Xiang China

I‐Jen Chiang Taiwan

Giuseppe Tradigo Italy

Hasan Oğul Türkiye

Yen‐Jen Oyang Taiwan

Hany Alashwal United Arab Emirates

Mingquan Ye

194 ×1.1

AI

189 ×1.2

MB

30 ×0.4

CVPR

39 ×0.5

RNMI

51 ×0.9

CTM

Citations per year, relative to Mingquan Ye Mingquan Ye (= 1×) peers Hany Alashwal

Countries citing papers authored by Mingquan Ye

Since Specialization

Citations

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

Fields of papers citing papers by Mingquan Ye

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingquan Ye

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Yang, Lingfei, et al.. (2025). An explainable machine learning model for predicting chronic coronary disease and identifying valuable text features. Frontiers in Cardiovascular Medicine. 12. 1559831–1559831.

2.

Liu, Heng, et al.. (2025). Improving bi-directional recurrent network for video super-resolution with deformable motion alignment structure. International Journal of Machine Learning and Cybernetics. 16(7-8). 4783–4795.

3.

Yang, Hui, et al.. (2024). Enhancing metastatic colorectal cancer prediction through advanced feature selection and machine learning techniques. International Immunopharmacology. 142(Pt A). 113033–113033. 3 indexed citations

4.

Liu, Juntong, et al.. (2024). Intracranial aneurysm detection based on 3D point cloud object detection method. Cogent Engineering. 11(1). 1 indexed citations

5.

Wang, Tingting, et al.. (2024). Nonlinear analysis and recognition of epileptic EEG signals in different stages. Journal of Neurophysiology. 132(3). 685–694. 5 indexed citations

6.

Wang, Tingting, et al.. (2023). Study on characteristic of epileptic multi-electroencephalograph base on Hilbert-Huang transform and brain network dynamics. Frontiers in Neuroscience. 17. 1117340–1117340. 5 indexed citations

7.

Wang, Lu, et al.. (2023). Changing trends in the global burden of mental disorders from 1990 to 2019 and predicted levels in 25 years. Epidemiology and Psychiatric Sciences. 32. e63–e63. 66 indexed citations breakdown →

8.

Fang, Fang, et al.. (2022). m6A RNA methylation regulator-based signature for prognostic prediction and its potential immunological role in uterine corpus endometrial carcinoma. BMC Cancer. 22(1). 1364–1364. 7 indexed citations

9.

Li, Qingqing, Hui Yang, Peipei Wang, et al.. (2022). XGBoost-based and tumor-immune characterized gene signature for the prediction of metastatic status in breast cancer. Journal of Translational Medicine. 20(1). 177–177. 56 indexed citations

10.

Li, Qingqing, et al.. (2022). A two-stage hybrid gene selection algorithm combined with machine learning models to predict the rupture status in intracranial aneurysms. Frontiers in Neuroscience. 16. 1034971–1034971. 3 indexed citations

11.

Chen, Yue, et al.. (2022). SRV-GAN: A generative adversarial network for segmenting retinal vessels. Mathematical Biosciences & Engineering. 19(10). 9948–9965. 11 indexed citations

12.

Chen, Guozhong, et al.. (2022). Mr.Vc v2: An updated version of database with increased data of transcriptome and experimental validated interactions. Frontiers in Microbiology. 13. 1047259–1047259. 3 indexed citations

13.

Ye, Mingquan, et al.. (2021). Informative Gene Selection Based on Cost-Sensitive Fast Correlation- Based Filter Feature Selection. Current Bioinformatics. 16(8). 1060–1068. 6 indexed citations

14.

Su, Run, Jinhuai Liu, Deyun Zhang, Chuandong Cheng, & Mingquan Ye. (2020). Multimodal Glioma Image Segmentation Using Dual Encoder Structure and Channel Spatial Attention Block. Frontiers in Neuroscience. 14. 586197–586197. 9 indexed citations

15.

Ye, Mingquan, et al.. (2017). Brain MR image segmentation based on Gaussian filtering and improved FCM clustering algorithm. 1–5. 12 indexed citations

16.

Gao, Lingyun, et al.. (2017). Cancer Classification Based on Support Vector Machine Optimized by Particle Swarm Optimization and Artificial Bee Colony. Molecules. 22(12). 2086–2086. 36 indexed citations

17.

Wu, Xindong, Mingquan Ye, Donghui Hu, et al.. (2012). Pervasive Medical Information Management and Services: Key Techniques and Challenges. Chinese Journal of Computers. 35(5). 827–845. 4 indexed citations

18.

Ye, Mingquan. (2008). The Research of Classfication Model Based on Rough Sets and RBF Neural Network. 1 indexed citations

19.

Ye, Mingquan. (2007). Application of data mining in medical diagnosis data.

20.

Ye, Mingquan & Xuegang Hu. (2005). Seasonal Artificial Neural Network Forecasting Model and its Application in the GM(1, 1) Residual Error Correction. Computer Engineering and Applications Journal. 41(1). 194–196. 1 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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