Zhenyu Tang

4.2k total citations
98 papers, 2.8k citations indexed

About

Zhenyu Tang is a scholar working on Computer Vision and Pattern Recognition, Neurology and Surgery. According to data from OpenAlex, Zhenyu Tang has authored 98 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 15 papers in Neurology and 12 papers in Surgery. Recurrent topics in Zhenyu Tang's work include Medical Image Segmentation Techniques (13 papers), Brain Tumor Detection and Classification (8 papers) and Advanced Neural Network Applications (6 papers). Zhenyu Tang is often cited by papers focused on Medical Image Segmentation Techniques (13 papers), Brain Tumor Detection and Classification (8 papers) and Advanced Neural Network Applications (6 papers). Zhenyu Tang collaborates with scholars based in China, United States and South Korea. Zhenyu Tang's co-authors include Wen-Shang Hou, Min Li, Yingli Fan, Xiaowei Zhang, Xiaowei Zhang, Tom Kadesch, Min Li, Peter Ordentlich, Chris Kintner and Ronald M. Evans and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Genes & Development.

In The Last Decade

Zhenyu Tang

86 papers receiving 2.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhenyu Tang China 27 793 310 304 294 262 98 2.8k
Tetsu Watanabe Japan 37 907 1.1× 611 2.0× 442 1.5× 347 1.2× 181 0.7× 270 5.0k
Corinne D. Engelman United States 32 970 1.2× 1.0k 3.3× 75 0.2× 147 0.5× 422 1.6× 112 3.6k
Lixiang Lin China 16 687 0.9× 455 1.5× 174 0.6× 142 0.5× 437 1.7× 34 3.5k
Huijun Wang China 30 1.1k 1.4× 220 0.7× 52 0.2× 132 0.4× 120 0.5× 201 4.2k
Wei Luo China 29 662 0.8× 225 0.7× 146 0.5× 258 0.9× 44 0.2× 217 2.6k
Maurizio Bevilacqua Italy 33 760 1.0× 555 1.8× 135 0.4× 165 0.6× 110 0.4× 159 4.2k
Wei Han China 32 1.3k 1.6× 285 0.9× 63 0.2× 136 0.5× 296 1.1× 177 3.1k
Lu Liu China 29 1.2k 1.5× 310 1.0× 47 0.2× 69 0.2× 94 0.4× 195 3.8k
Hideki Kato Japan 35 1.6k 2.1× 247 0.8× 678 2.2× 67 0.2× 87 0.3× 153 3.9k
Takayuki Hidaka Japan 28 294 0.4× 236 0.8× 74 0.2× 158 0.5× 138 0.5× 102 2.6k

Countries citing papers authored by Zhenyu Tang

Since Specialization
Citations

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

Fields of papers citing papers by Zhenyu Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhenyu Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Zhenyu Tang. A scholar is included among the top collaborators of Zhenyu Tang 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 Zhenyu Tang. Zhenyu Tang 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.
Zhang, Liping, Qin Zhang, Yi Li, et al.. (2025). Decrease in urban-rural differences of nighttime humid heatwaves in the Yangtze River Delta, China. Atmospheric Research. 316. 107956–107956. 1 indexed citations
2.
3.
Chen, Zhiying, Chuang Liu, Zhenyu Tang, et al.. (2024). Vision-based trajectory generation and tracking algorithm for maneuvering of a paddy field robot. Computers and Electronics in Agriculture. 226. 109368–109368. 5 indexed citations
4.
Liu, Xinwen, Weilin Jin, Wei Xia, et al.. (2024). Multi-task learning for calcaneus fracture diagnosis of X-ray images. Biomedical Signal Processing and Control. 99. 106843–106843. 3 indexed citations
5.
Zhang, Liping, Gangsheng Wang, Qin Zhang, et al.. (2024). Impacts of urban expansion on air temperature and humidity during 2022 mega-heatwave over the Yangtze River Delta, China. The Science of The Total Environment. 951. 175804–175804. 2 indexed citations
6.
Wang, Guanhua, et al.. (2024). Sevoflurane causes neurotoxicity and cognitive impairment by regulating Hippo signaling pathway-mediated ferroptosis via upregulating PRKCD. Experimental Neurology. 377. 114804–114804. 4 indexed citations
7.
Fang, Haoshu, Hongjie Fang, Zhenyu Tang, et al.. (2024). RH20T: A Comprehensive Robotic Dataset for Learning Diverse Skills in One-Shot. 653–660. 29 indexed citations
8.
Liu, Huabing, et al.. (2024). Multimodal Brain Tumor Segmentation Boosted by Monomodal Normal Brain Images. IEEE Transactions on Image Processing. 33. 1199–1210. 15 indexed citations
9.
Wang, Yan, et al.. (2024). Combined healthy lifestyle behaviors and all-cause mortality risk in middle-aged and older US adults: A longitudinal cohort study. Archives of Gerontology and Geriatrics. 130. 105702–105702. 1 indexed citations
10.
Liu, Chuang, et al.. (2023). Benefits of mechanical weeding for weed control, rice growth characteristics and yield in paddy fields. Field Crops Research. 293. 108852–108852. 26 indexed citations
11.
12.
He, Kelei, Wei Zhao, Xingzhi Xie, et al.. (2021). Synergistic learning of lung lobe segmentation and hierarchical multi-instance classification for automated severity assessment of COVID-19 in CT images. Pattern Recognition. 113. 107828–107828. 78 indexed citations
13.
Tang, Zhenyu, Yuyun Xu, Lei Jin, et al.. (2020). Deep Learning of Imaging Phenotype and Genotype for Predicting Overall Survival Time of Glioblastoma Patients. IEEE Transactions on Medical Imaging. 39(6). 2100–2109. 67 indexed citations
14.
Li, Yang, Jingyu Liu, Zhenyu Tang, & Baiying Lei. (2020). Deep Spatial-Temporal Feature Fusion From Adaptive Dynamic Functional Connectivity for MCI Identification. IEEE Transactions on Medical Imaging. 39(9). 2818–2830. 109 indexed citations
15.
Zhu, Hancan, et al.. (2019). Multi-atlas label fusion with random local binary pattern features: Application to hippocampus segmentation. Scientific Reports. 9(1). 16839–16839. 13 indexed citations
16.
Li, Min�, et al.. (2016). Impact of Retinal Vein Occlusion on Stroke Incidence: A Meta‐Analysis. Journal of the American Heart Association. 5(12). 26 indexed citations
17.
Li, Min, et al.. (2016). Shift work and risk of stroke: A meta-analysis. International Journal of Cardiology. 214. 370–373. 27 indexed citations
18.
Li, Min, Yingli Fan, Xiaowei Zhang, Wen-Shang Hou, & Zhenyu Tang. (2014). Fruit and vegetable intake and risk of type 2 diabetes mellitus: meta-analysis of prospective cohort studies. BMJ Open. 4(11). e005497–e005497. 301 indexed citations
19.
Li, Min, Wen-Shang Hou, Xiaowei Zhang, & Zhenyu Tang. (2014). Obstructive sleep apnea and risk of stroke: A meta-analysis of prospective studies. International Journal of Cardiology. 172(2). 466–469. 84 indexed citations
20.
Kishi, Noriyuki, Zhenyu Tang, Yusuke T. Maeda, et al.. (2001). Murine homologs of deltex define a novel gene family involved in vertebrate Notch signaling and neurogenesis. International Journal of Developmental Neuroscience. 19(1). 21–35. 82 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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