Lisheng Wang

3.9k total citations
139 papers, 2.6k citations indexed

About

Lisheng Wang is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Cancer Research. According to data from OpenAlex, Lisheng Wang has authored 139 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Radiology, Nuclear Medicine and Imaging, 40 papers in Computer Vision and Pattern Recognition and 23 papers in Cancer Research. Recurrent topics in Lisheng Wang's work include Radiomics and Machine Learning in Medical Imaging (21 papers), Medical Image Segmentation Techniques (19 papers) and Retinal Imaging and Analysis (14 papers). Lisheng Wang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (21 papers), Medical Image Segmentation Techniques (19 papers) and Retinal Imaging and Analysis (14 papers). Lisheng Wang collaborates with scholars based in China, United States and Australia. Lisheng Wang's co-authors include Fengjun Xiao, Zongben Xu, Yuefeng Yang, Huai Chen, Shaoli Song, Yijie Huang, Hua Wang, Xiuying Wang, Yau‐Huei Wei and Chun‐Ming Tsai and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and Blood.

In The Last Decade

Lisheng Wang

130 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lisheng Wang China 24 952 777 673 331 279 139 2.6k
Ming Y. Lu United States 33 1.3k 1.4× 430 0.6× 1.4k 2.0× 235 0.7× 433 1.6× 76 4.7k
Xiaohua Qian China 24 383 0.4× 279 0.4× 619 0.9× 190 0.6× 343 1.2× 82 1.7k
Tetsuya Higuchi Japan 30 880 0.9× 520 0.7× 896 1.3× 614 1.9× 93 0.3× 181 3.8k
Zheng Liu China 31 1.8k 1.9× 275 0.4× 561 0.8× 181 0.5× 160 0.6× 180 4.2k
Kar‐Ming Fung United States 31 924 1.0× 376 0.5× 389 0.6× 462 1.4× 134 0.5× 116 3.2k
Arnout Ruifrok Netherlands 21 791 0.8× 203 0.3× 582 0.9× 415 1.3× 502 1.8× 48 3.2k
Zhen Qian China 22 494 0.5× 188 0.2× 370 0.5× 144 0.4× 281 1.0× 79 1.7k
Jun Xia China 25 523 0.5× 267 0.3× 2.0k 3.0× 464 1.4× 378 1.4× 124 4.0k
D. A. Johnston United States 20 1.2k 1.2× 294 0.4× 470 0.7× 516 1.6× 364 1.3× 43 4.0k
Wenjun Liao China 26 581 0.6× 463 0.6× 306 0.5× 317 1.0× 236 0.8× 156 2.3k

Countries citing papers authored by Lisheng Wang

Since Specialization
Citations

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

Fields of papers citing papers by Lisheng Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lisheng Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Lisheng Wang. A scholar is included among the top collaborators of Lisheng 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 Lisheng Wang. Lisheng 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.
Chen, Xuming, Fanrui Meng, Ping Zhang, et al.. (2025). Establishing a Deep Learning Model That Integrates Pretreatment and Midtreatment Computed Tomography to Predict Treatment Response in Non-Small Cell Lung Cancer. International Journal of Radiation Oncology*Biology*Physics. 122(5). 1380–1390. 1 indexed citations
2.
Qian, Tianwei, et al.. (2024). ClarityDiffuseNet: Enhancing fundus image quality under black shadows with diffusion model-based research. Pattern Recognition Letters. 186. 279–285. 2 indexed citations
3.
4.
Chen, Huai, Xiuying Wang, Jieyu Li, et al.. (2023). Unsupervised Local Discrimination for Medical Images. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(12). 15912–15929. 4 indexed citations
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Wang, Lisheng, Deyu Meng, Hao Liu, et al.. (2022). Individualized Statistical Modeling of Lesions in Fundus Images for Anomaly Detection. IEEE Transactions on Medical Imaging. 42(4). 1185–1196. 2 indexed citations
8.
Wang, Xun, Lisheng Wang, & Pan Zheng. (2022). SC-Dynamic R-CNN: A Self-Calibrated Dynamic R-CNN Model for Lung Cancer Lesion Detection. Computational and Mathematical Methods in Medicine. 2022. 1–9. 13 indexed citations
9.
Xin, Bowen, Ziyi Yang, Junyan Xu, et al.. (2022). Radiomic analysis for predicting prognosis of colorectal cancer from preoperative 18F-FDG PET/CT. Journal of Translational Medicine. 20(1). 66–66. 37 indexed citations
10.
Zhang, Jian, et al.. (2022). Identification of lncRNA DLEU2 as a potential diagnostic biomarker and anti-inflammatory target for ulcerative colitis. Frontiers in Pharmacology. 13. 991448–991448. 7 indexed citations
11.
Bao, Guoqing, Huai Chen, Tongliang Liu, et al.. (2021). COVID-MTL: Multitask learning with Shift3D and random-weighted loss for COVID-19 diagnosis and severity assessment. Pattern Recognition. 124. 108499–108499. 21 indexed citations
12.
Xu, Zhenglei, Weixiang Luo, Ruiyue Shi, et al.. (2021). MicroRNA-505, Suppressed by Oncogenic Long Non-coding RNA LINC01448, Acts as a Novel Suppressor of Glycolysis and Tumor Progression Through Inhibiting HK2 Expression in Pancreatic Cancer. Frontiers in Cell and Developmental Biology. 8. 625056–625056. 17 indexed citations
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Wang, Hao, Weidong Xu, Tao Wang, et al.. (2018). Oncolytic Adenovirus rAd.DCN Inhibits Breast Tumor Growth and Lung Metastasis in an Immune-Competent Orthotopic Xenograft Model. Human Gene Therapy. 30(2). 197–210. 22 indexed citations
15.
Hu, Wei, et al.. (2018). Design, synthesis and evaluation of a novel fluorescent probe to accurately detect H 2 S in lysosomes. Tetrahedron Letters. 59(27). 2683–2687. 11 indexed citations
16.
Yang, Heran, Jian Sun, Huibin Li, Lisheng Wang, & Zongben Xu. (2018). Neural multi-atlas label fusion: Application to cardiac MR images. Medical Image Analysis. 49. 60–75. 21 indexed citations
17.
Wang, Lisheng, Ling Li, Liang Li, et al.. (2010). MicroRNA-486-5p Targets Foxo1 and Regulates Human Hematopoietic Stem Cell Proliferation and Erythroid Differentiation. Blood. 116(21). 3871–3871. 1 indexed citations
18.
Cui, Chun‐Ping, Shaojun Du, Danli Wu, et al.. (2008). Isolation and functional identification of a novel human hepatic growth factor: Hepatopoietin Cn. Hepatology. 47(3). 986–995. 14 indexed citations
19.
Chen, Lin, Tao Li, Rong Li, et al.. (2006). [Inhibition of alphastatin on angiogenesis in human endothelial cells and the mechanism thereof: an experimental study].. PubMed. 86(15). 1061–4. 1 indexed citations
20.
Yang, Eric V., Lisheng Wang, & Roy A. Tassava. (2005). Effects of exogenous FGF-1 treatment on regeneration of the lens and the neural retina in the Newt,Notophthalmus viridescens. Journal of Experimental Zoology Part A Comparative Experimental Biology. 303A(10). 837–844. 2 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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