Wei Wang

17.7k total citations · 1 hit paper
657 papers, 12.2k citations indexed

About

Wei Wang is a scholar working on Surgery, Pulmonary and Respiratory Medicine and Epidemiology. According to data from OpenAlex, Wei Wang has authored 657 papers receiving a total of 12.2k indexed citations (citations by other indexed papers that have themselves been cited), including 202 papers in Surgery, 157 papers in Pulmonary and Respiratory Medicine and 136 papers in Epidemiology. Recurrent topics in Wei Wang's work include Liver Disease Diagnosis and Treatment (86 papers), Hepatocellular Carcinoma Treatment and Prognosis (84 papers) and Radiomics and Machine Learning in Medical Imaging (69 papers). Wei Wang is often cited by papers focused on Liver Disease Diagnosis and Treatment (86 papers), Hepatocellular Carcinoma Treatment and Prognosis (84 papers) and Radiomics and Machine Learning in Medical Imaging (69 papers). Wei Wang collaborates with scholars based in China, United States and Japan. Wei Wang's co-authors include Xiaoyan Xie, Ming‐De Lu, Ming Kuang, Li‐Da Chen, Ming Xu, Yang Huang, Shi‐Ting Feng, Duojia Pan, Jinyu Liang and Shuling Chen and has published in prestigious journals such as JAMA, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Wei Wang

612 papers receiving 12.1k citations

Hit Papers

Predicting peritoneal recurrence and disease-free surviva... 2022 2026 2023 2024 2022 25 50 75 100

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wei Wang China 54 2.9k 2.5k 2.2k 2.1k 2.1k 657 12.2k
Ping Liang China 53 1.5k 0.5× 1.4k 0.6× 2.5k 1.1× 1.9k 0.9× 3.2k 1.6× 483 9.8k
Hiroshi Yoshida Japan 55 2.6k 0.9× 719 0.3× 3.7k 1.6× 1.9k 0.9× 2.0k 1.0× 869 14.3k
Peter Boor Germany 62 5.2k 1.8× 1.5k 0.6× 1.8k 0.8× 1.9k 0.9× 429 0.2× 449 14.7k
Atsushi Takahashi Japan 74 4.6k 1.6× 1.1k 0.5× 2.8k 1.2× 2.0k 1.0× 623 0.3× 487 19.5k
Gang Huang China 49 4.5k 1.6× 1.6k 0.6× 989 0.4× 1.4k 0.7× 755 0.4× 389 9.8k
Tae Hyun Kim South Korea 54 1.5k 0.5× 1.6k 0.6× 3.6k 1.6× 3.0k 1.5× 1.4k 0.7× 452 10.8k
Tom Luedde Germany 65 5.4k 1.9× 1.3k 0.5× 2.5k 1.1× 1.3k 0.6× 5.0k 2.4× 377 18.5k
Chun‐Ying Wu Taiwan 60 2.8k 1.0× 680 0.3× 4.5k 2.0× 1.5k 0.7× 2.1k 1.0× 286 14.9k
Bin Zhang China 52 1.9k 0.6× 2.3k 0.9× 1.8k 0.8× 1.6k 0.8× 306 0.1× 673 11.8k
Myeong‐Jin Kim South Korea 64 1.5k 0.5× 4.4k 1.8× 5.3k 2.4× 3.1k 1.5× 4.8k 2.3× 615 15.6k

Countries citing papers authored by Wei Wang

Since Specialization
Citations

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

Fields of papers citing papers by Wei Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wei Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Wei Wang. A scholar is included among the top collaborators of Wei 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 Wei Wang. Wei 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
2.
Tong, Wenjuan, Yihao Liu, Rui Cui, et al.. (2025). Adaptive Dual-Task Deep Learning for Automated Thyroid Cancer Triaging at Screening US. Radiology Artificial Intelligence. 7(3). e240271–e240271. 2 indexed citations
3.
Li, Ming‐De, Wei Li, Manxia Lin, et al.. (2024). Systematic comparison of deep-learning based fusion strategies for multi-modal ultrasound in diagnosis of liver cancer. Neurocomputing. 603. 128257–128257. 8 indexed citations
4.
Tang, Hongmei, et al.. (2024). Interaction effects on acoustic emissions of submicron ultrasound contrast agents at subharmonic resonances. Ultrasonics. 148. 107553–107553. 2 indexed citations
5.
Wang, Wentao, Qing Wang, Wenming Li, et al.. (2024). Targeting APJ drives BNIP3-PINK1-PARKIN induced mitophagy and improves systemic inflammatory bone loss. Journal of Advanced Research. 76. 655–668. 4 indexed citations
6.
Wang, Biying, et al.. (2024). Flavonoids analysis in citrus peels by UPLC-Q-TOF-MS/MS and its antioxidant and anti-inflammation activity. SHILAP Revista de lepidopterología. 5. 100853–100853. 5 indexed citations
7.
Li, Ming‐De, Si‐Min Ruan, Li‐Da Chen, et al.. (2023). ADMNet: Adaptive-Weighting Dual Mapping for Online Tracking With Respiratory Motion Estimation in Contrast-Enhanced Ultrasound. IEEE Transactions on Image Processing. 33. 58–68. 4 indexed citations
8.
Jiang, Yuming, Kangneng Zhou, Zepang Sun, et al.. (2023). Non-invasive tumor microenvironment evaluation and treatment response prediction in gastric cancer using deep learning radiomics. Cell Reports Medicine. 4(8). 101146–101146. 62 indexed citations
9.
Zheng, Yaozong, et al.. (2023). A general maximal margin hyper-sphere SVM for multi-class classification. Expert Systems with Applications. 237. 121647–121647. 15 indexed citations
10.
Wang, Xiaoxiao, Xiu‐Qing Li, Chenxi Wang, et al.. (2021). Prediction of BRCA Gene Mutation in Breast Cancer Based on Deep Learning and Histopathology Images. Frontiers in Genetics. 12. 661109–661109. 47 indexed citations
11.
Jones, Brett D. M., Robert D. Levitan, Wei Wang, et al.. (2021). Metabolic variables associated with response to cognitive behavioural therapy for depression in females: A Canadian biomarker integration network for depression (CAN-BIND) study. Journal of Psychiatric Research. 142. 321–327. 1 indexed citations
13.
Luo, Zhe, Xiaohui Wang, Shaoxin Wang, et al.. (2019). Clinical characteristics and risk factor analysis of delayed bleeding after endoscopic mucosal resection for colon polyps. SHILAP Revista de lepidopterología. 44(9). 779–783. 1 indexed citations
14.
Li, Wei, Jinyu Liang, Xin Li, et al.. (2019). Ultrasomics for Early Evaluation of the Tumor Response to MicroRNA‐122 in a Nude Mouse Hepatocellular Carcinoma Model. Journal of Ultrasound in Medicine. 39(1). 61–71. 2 indexed citations
15.
Zhang, Jianchao, Zhu Wang, Si‐Min Ruan, et al.. (2019). Assessment of angiogenesis in rabbit orthotropic liver tumors using three-dimensional dynamic contrast-enhanced ultrasound compared with two-dimensional DCE-US. Japanese Journal of Radiology. 37(10). 701–709. 3 indexed citations
16.
Chen, Wen, Qi Zhang, Wei Wang, et al.. (2019). Shift of Reference Values for Thyroid Volume by Ultrasound in 8- to 13-Year-Olds with Sufficient Iodine Intake in China. Thyroid. 29(3). 405–411. 8 indexed citations
17.
Wang, Wei, Mingjiang Xu, Yan Cai, et al.. (2017). Inflammation is independent of steatosis in a murine model of steatohepatitis. Hepatology. 66(1). 108–123. 59 indexed citations
18.
Wang, Wei, Lu Hao, & Xingang Shi. (2017). Therapeutic value of endoscopic papillectomy for duodenal papilla lesion. Zhonghua xiaohua neijing zazhi. 34(7). 480–484.
19.
Chen, Li‐Da, Zhu Wang, Yang Huang, et al.. (2016). Hilar biliary neurofibroma without neurofibromatosis: case report with contrast-enhanced ultrasound findings. Journal of Medical Ultrasonics. 43(4). 537–543. 1 indexed citations
20.
Dai, Lixia, Wei Wang, Shuang Zhang, et al.. (2012). Vector‐based miR‐15a/16‐1 plasmid inhibits colon cancer growth in vivo. Cell Biology International. 36(8). 765–770. 34 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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