Hongyu Wang

1.2k total citations · 1 hit paper
70 papers, 779 citations indexed

About

Hongyu Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Hongyu Wang has authored 70 papers receiving a total of 779 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 19 papers in Artificial Intelligence and 17 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Hongyu Wang's work include Radiomics and Machine Learning in Medical Imaging (13 papers), AI in cancer detection (10 papers) and Medical Image Segmentation Techniques (5 papers). Hongyu Wang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (13 papers), AI in cancer detection (10 papers) and Medical Image Segmentation Techniques (5 papers). Hongyu Wang collaborates with scholars based in China, United States and United Kingdom. Hongyu Wang's co-authors include Jun Feng, Songtao Ding, Shaohua Wan, Xiaoying Pan, Lang He, Mingyue Niu, Lei Cui, Prayag Tiwari, Jiewei Jiang and Chenguang Guo and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Frontiers in Immunology.

In The Last Decade

Hongyu Wang

61 papers receiving 751 citations

Hit Papers

Deep learning for depress... 2021 2026 2022 2024 2021 40 80 120

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hongyu Wang China 15 251 234 174 106 79 70 779
Ajay Mittal India 17 276 1.1× 311 1.3× 397 2.3× 76 0.7× 32 0.4× 48 1.0k
Ninad Mehendale India 17 332 1.3× 400 1.7× 380 2.2× 169 1.6× 81 1.0× 90 1.2k
Mohamed Hédi Bedoui Tunisia 15 182 0.7× 266 1.1× 233 1.3× 56 0.5× 158 2.0× 124 927
Yu Qiao China 15 134 0.5× 113 0.5× 233 1.3× 20 0.2× 45 0.6× 56 827
Ganbayar Batchuluun South Korea 17 204 0.8× 192 0.8× 363 2.1× 25 0.2× 31 0.4× 34 777
Yufei Ye China 13 350 1.4× 76 0.3× 401 2.3× 28 0.3× 33 0.4× 28 941
María Teresa Garcí­a-Ordás Spain 16 202 0.8× 57 0.2× 64 0.4× 20 0.2× 90 1.1× 47 727
Fenglian Li China 16 206 0.8× 36 0.2× 96 0.6× 25 0.2× 138 1.7× 67 751
Hayaru Shouno Japan 11 155 0.6× 61 0.3× 176 1.0× 11 0.1× 67 0.8× 59 597
Malaya Kumar Nath India 21 375 1.5× 534 2.3× 493 2.8× 59 0.6× 16 0.2× 67 1.3k

Countries citing papers authored by Hongyu Wang

Since Specialization
Citations

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

Fields of papers citing papers by Hongyu Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hongyu Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Hongyu Wang. A scholar is included among the top collaborators of Hongyu 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 Hongyu Wang. Hongyu 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.
Wang, Hongyu, Yonghao Long, Hon‐Chi Yip, et al.. (2025). Learning dissection trajectories from expert surgical videos via imitation learning with equivariant diffusion. Medical Image Analysis. 103. 103599–103599. 1 indexed citations
2.
Wang, Hongyu, et al.. (2025). A Multi-Sequence MRI-Based Hierarchical Expert Diagnostic Method for the Molecular Subtype of Breast Cancer. IEEE Journal of Biomedical and Health Informatics. 29(4). 2885–2898.
4.
Zhang, Xiaodan, et al.. (2025). A Multisource Precipitation Data Fusion Model for Qinghai Province Based on 3D CNN and Bidirectional ConvLSTM. Journal of Hydrometeorology. 26(3). 327–343.
5.
Wang, Hongyu, et al.. (2025). Study on the Fire Suppression Efficiency of Common Extinguishing Agents for Lithium Iron Phosphate Battery Fires. Fire Technology. 61(6). 4059–4079. 6 indexed citations
6.
Li, Xue, Yan Fu, Guolian Zhu, et al.. (2025). Identification and validation of an explainable machine learning model for hepatocellular carcinoma at high risk: a retrospective multicenter cohort study. International Journal of Surgery. 112(1). 1164–1176.
7.
Wang, Lu, et al.. (2024). Diagnostic study of nitrogen nutrition in cotton based on unmanned aerial vehicle RGB images. Notulae Botanicae Horti Agrobotanici Cluj-Napoca. 52(2). 13728–13728.
8.
Wang, Hongyu, et al.. (2024). Construction of cotton leaf nitrogen content estimation model based on the PROSPECT model. Notulae Botanicae Horti Agrobotanici Cluj-Napoca. 52(1). 13565–13565. 1 indexed citations
9.
Wang, Hongyu, Ting Liu, Yaoming Chen, et al.. (2024). Peripheral blood lymphocyte subsets predict the efficacy of TACE with or without PD-1 inhibitors in patients with hepatocellular carcinoma: a prospective clinical study. Frontiers in Immunology. 15. 1325330–1325330. 2 indexed citations
10.
Wang, Hongyu, Dandan Zhang, Jun Feng, et al.. (2023). A multi-objective segmentation method for chest X-rays based on collaborative learning from multiple partially annotated datasets. Information Fusion. 102. 102016–102016. 17 indexed citations
11.
Wang, Hongyu, et al.. (2023). Feature-enhanced multi-sequence MRI-based fusion mechanism for breast tumor segmentation. Biomedical Signal Processing and Control. 90. 105886–105886. 1 indexed citations
12.
Zhang, Dandan, et al.. (2023). CAMS-Net: An attention-guided feature selection network for rib segmentation in chest X-rays. Computers in Biology and Medicine. 156. 106702–106702. 4 indexed citations
13.
Wang, Hongyu, Henry Gouk, Eibe Frank, et al.. (2022). Experiments in cross‐domain few‐shot learning for image classification. Journal of the Royal Society of New Zealand. 53(1). 169–191. 3 indexed citations
14.
Sun, Xia, et al.. (2022). Neural network fusion with fine-grained adaptation learning for turnover prediction. Complex & Intelligent Systems. 9(3). 3355–3366.
15.
Pan, Xiaoying, et al.. (2022). Temporal-based Swin Transformer network for workflow recognition of surgical video. International Journal of Computer Assisted Radiology and Surgery. 18(1). 139–147. 11 indexed citations
16.
Huang, Li‐Ling, Xingsheng Hu, Yan Wang, et al.. (2021). Survival and pretreatment prognostic factors for extensive‐stage small cell lung cancer: A comprehensive analysis of 358 patients. Thoracic Cancer. 12(13). 1943–1951. 29 indexed citations
17.
Wang, Hongyu, et al.. (2020). Computer-Aided System for the Detection of Multicategory Pulmonary Tuberculosis in Radiographs. Journal of Healthcare Engineering. 2020. 1–12. 37 indexed citations
18.
Wang, Hongyu. (2011). An application of Hadoop platform in cloud computing. 2 indexed citations
19.
Wang, Hongyu. (2005). S-Rough sets and its F-memory. Journal of Shandong University. 2 indexed citations
20.
Wang, Hongyu. (2004). Fractional Lower Order α-Stable Distribution and Issues in Its Applications. Tance yu kongzhi xuebao.

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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