Wei Shao

3.0k total citations
105 papers, 1.8k citations indexed

About

Wei Shao is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Wei Shao has authored 105 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 27 papers in Computer Vision and Pattern Recognition and 20 papers in Artificial Intelligence. Recurrent topics in Wei Shao's work include AI in cancer detection (15 papers), Medical Image Segmentation Techniques (13 papers) and Radiomics and Machine Learning in Medical Imaging (12 papers). Wei Shao is often cited by papers focused on AI in cancer detection (15 papers), Medical Image Segmentation Techniques (13 papers) and Radiomics and Machine Learning in Medical Imaging (12 papers). Wei Shao collaborates with scholars based in China, United States and Singapore. Wei Shao's co-authors include Daoqiang Zhang, Liang Sun, Kun Huang, Jie Zhang, Tongxin Wang, Zixiao Lu, Meiling Wang, Mingliang Wang, Zhi Han and Chen Zu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and Nature Communications.

In The Last Decade

Wei Shao

98 papers receiving 1.8k citations

Peers

Wei Shao
Brett A. McKinney United States
David van Dijk United States
Axel Wismüller United States
Fang Li China
Vasileios Megalooikonomou Greece
Tanvir Alam Qatar
Yang Huang China
Chengyan Wang China
Yi Gao China
Brett A. McKinney United States
Wei Shao
Citations per year, relative to Wei Shao Wei Shao (= 1×) peers Brett A. McKinney

Countries citing papers authored by Wei Shao

Since Specialization
Citations

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

Fields of papers citing papers by Wei Shao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wei Shao

This figure shows the co-authorship network connecting the top 25 collaborators of Wei Shao. A scholar is included among the top collaborators of Wei Shao 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 Shao. Wei Shao 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.
Sun, Liang, Zhi Sun, Wei Shao, et al.. (2025). Edge-enhanced semi-supervised vertical convolutional neural network for tubular structure segmentation: Application to medical images. Pattern Recognition. 162. 111302–111302. 2 indexed citations
2.
Zhu, Qi, Ting Zhu, Lunke Fei, et al.. (2025). Multi-Modal Cross-Subject Emotion Feature Alignment and Recognition With EEG and Eye Movements. IEEE Transactions on Affective Computing. 16(3). 2102–2115. 2 indexed citations
3.
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5.
Cheng, Xi, et al.. (2023). A global–local attention network for uncertainty analysis of ground penetrating radar modeling. Reliability Engineering & System Safety. 234. 109176–109176. 3 indexed citations
6.
Wang, Meiling, Wei Shao, Shuo Huang, & Daoqiang Zhang. (2023). Hypergraph-regularized multimodal learning by graph diffusion for imaging genetics based Alzheimer’s Disease diagnosis. Medical Image Analysis. 89. 102883–102883. 23 indexed citations
7.
Shao, Wei, Yangyang Shi, Yawen Wu, et al.. (2023). Characterizing the Survival-Associated Interactions Between Tumor-Infiltrating Lymphocytes and Tumors From Pathological Images and Multi-Omics Data. IEEE Transactions on Medical Imaging. 42(10). 3025–3035. 9 indexed citations
8.
Zhu, Qi, et al.. (2023). MSTGC: Multi-Channel Spatio-Temporal Graph Convolution Network for Multi-Modal Brain Networks Fusion. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31. 2359–2369. 14 indexed citations
9.
Zhao, Yulai, Xuewei Bao, Joseph C. Wu, et al.. (2023). Single-cell RNA sequencing-guided fate-mapping toolkit delineates the contribution of yolk sac erythro-myeloid progenitors. Cell Reports. 42(11). 113364–113364. 11 indexed citations
10.
Zhu, Qi, et al.. (2022). Multimodal Triplet Attention Network for Brain Disease Diagnosis. IEEE Transactions on Medical Imaging. 41(12). 3884–3894. 36 indexed citations
11.
Zhu, Qi, et al.. (2022). Deep Multi-Modal Discriminative and Interpretability Network for Alzheimer’s Disease Diagnosis. IEEE Transactions on Medical Imaging. 42(5). 1472–1483. 40 indexed citations
12.
Liu, Ziyu, Travis S. Johnson, Wei Shao, et al.. (2022). Optimal transport- and kernel-based early detection of mild cognitive impairment patients based on magnetic resonance and positron emission tomography images. Alzheimer s Research & Therapy. 14(1). 4–4. 4 indexed citations
13.
Qi, Shile, Jing Sui, Godfrey D. Pearlson, et al.. (2022). Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network. Nature Communications. 13(1). 4929–4929. 30 indexed citations
14.
Lu, Zixiao, Xiaohui Zhan, Yi Wu, et al.. (2021). BrcaSeg : A Deep Learning Approach for Tissue Quantification and Genomic Correlations of Histopathological Images. Genomics Proteomics & Bioinformatics. 19(6). 1032–1042. 11 indexed citations
15.
Huang, Zhi, Zhi Han, Tongxin Wang, et al.. (2021). TSUNAMI: Translational Bioinformatics Tool Suite for Network Analysis and Mining. Genomics Proteomics & Bioinformatics. 19(6). 1023–1031. 10 indexed citations
16.
Boltz, Valerie F., Jason W. Rausch, Wei Shao, et al.. (2021). CpG Methylation Profiles of HIV-1 Proviral DNA in Individuals on ART. Viruses. 13(5). 799–799. 8 indexed citations
17.
Halvas, Elias K., Leah D. Brandt, Shuang Guo, et al.. (2020). HIV-1 viremia not suppressible by antiretroviral therapy can originate from large T cell clones producing infectious virus. Journal of Clinical Investigation. 130(11). 5847–5857. 87 indexed citations
18.
Peng, Hong, et al.. (2020). A three-stage method for batch-based incremental nonnegative matrix factorization. Neurocomputing. 400. 150–160. 6 indexed citations
19.
Lu, Zixiao, Wei Shao, Yi Wu, et al.. (2020). Deep-Learning–Based Characterization of Tumor-Infiltrating Lymphocytes in Breast Cancers From Histopathology Images and Multiomics Data. JCO Clinical Cancer Informatics. 4(4). 480–490. 65 indexed citations
20.
Shao, Wei, Valerie F. Boltz, Junko Hattori, et al.. (2020). Short Communication: HIV-DRLink: A Tool for Reporting Linked HIV-1 Drug Resistance Mutations in Large Single-Genome Data Sets Using the Stanford HIV Database. AIDS Research and Human Retroviruses. 36(11). 942–947. 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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