Hulin Kuang

1.7k total citations
57 papers, 1.1k citations indexed

About

Hulin Kuang is a scholar working on Epidemiology, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Hulin Kuang has authored 57 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Epidemiology, 18 papers in Computer Vision and Pattern Recognition and 16 papers in Artificial Intelligence. Recurrent topics in Hulin Kuang's work include Acute Ischemic Stroke Management (17 papers), Cerebrovascular and Carotid Artery Diseases (10 papers) and Radiomics and Machine Learning in Medical Imaging (9 papers). Hulin Kuang is often cited by papers focused on Acute Ischemic Stroke Management (17 papers), Cerebrovascular and Carotid Artery Diseases (10 papers) and Radiomics and Machine Learning in Medical Imaging (9 papers). Hulin Kuang collaborates with scholars based in China, Canada and Hong Kong. Hulin Kuang's co-authors include Wu Qiu, Bijoy K. Menon, Hong Yan, Leanne Lai Hang Chan, Long Chen, Sung‐Il Sohn, Mayank Goyal, Michael D. Hill, Andrew M. Demchuk and Jianxin Wang and has published in prestigious journals such as Stroke, Radiology and IEEE Access.

In The Last Decade

Hulin Kuang

48 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hulin Kuang China 20 439 414 245 211 192 57 1.1k
Jianhuang Wu China 21 380 0.9× 91 0.2× 197 0.8× 231 1.1× 379 2.0× 74 1.3k
Mohammed A. Al‐masni South Korea 17 443 1.0× 298 0.7× 127 0.5× 196 0.9× 813 4.2× 51 2.0k
Mun‐Taek Choi South Korea 13 345 0.8× 128 0.3× 86 0.4× 140 0.7× 474 2.5× 42 1.3k
Muhammad Haris Khan Pakistan 16 796 1.8× 36 0.1× 58 0.2× 167 0.8× 354 1.8× 71 1.5k
Mamta Juneja India 23 846 1.9× 51 0.1× 57 0.2× 293 1.4× 576 3.0× 83 1.8k
Justin Ker Singapore 5 356 0.8× 69 0.2× 87 0.4× 176 0.8× 537 2.8× 6 1.3k
Zhijian Song China 17 561 1.3× 45 0.1× 118 0.5× 296 1.4× 393 2.0× 87 1.2k
Marcos Ortega Spain 24 461 1.1× 100 0.2× 121 0.5× 302 1.4× 1.2k 6.3× 151 1.9k
Fangxu Xing United States 19 307 0.7× 64 0.2× 89 0.4× 65 0.3× 270 1.4× 75 872
Yinan Yu Sweden 16 998 2.3× 40 0.1× 50 0.2× 405 1.9× 156 0.8× 46 1.7k

Countries citing papers authored by Hulin Kuang

Since Specialization
Citations

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

Fields of papers citing papers by Hulin Kuang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hulin Kuang

This figure shows the co-authorship network connecting the top 25 collaborators of Hulin Kuang. A scholar is included among the top collaborators of Hulin Kuang 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 Hulin Kuang. Hulin Kuang 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.
Kuang, Hulin, et al.. (2025). FedComDist: Towards Effective Personalized Federated Learning for Patient Outcome Prediction Using Multi-Center Electronic Medical Records. IEEE Journal of Biomedical and Health Informatics. 29(8). 6004–6016.
2.
Liu, Jin, Hanhe Lin, Hulin Kuang, et al.. (2025). Multi-Modal Multi-Kernel Graph Learning for Autism Prediction and Biomarker Discovery. PubMed. 22(2). 842–854. 3 indexed citations
3.
Kuang, Hulin, Xinyuan Liu, Jin Liu, et al.. (2025). Large vessel occlusion identification network with vessel guidance and asymmetry learning on CT angiography of acute ischemic stroke patients. Medical Image Analysis. 101. 103490–103490. 2 indexed citations
4.
5.
Kuang, Hulin, Jialin Yang, Jiulou Zhang, et al.. (2025). LW-CTrans: A lightweight hybrid network of CNN and Transformer for 3D medical image segmentation. Medical Image Analysis. 102. 103545–103545. 7 indexed citations
6.
Shen, Chengchao, et al.. (2024). Asymmetric patch sampling for contrastive learning. Pattern Recognition. 158. 111012–111012. 3 indexed citations
7.
Kuang, Hulin, Fouzi Bala, Jianhai Zhang, et al.. (2024). Two-stage convolutional neural network for segmentation and detection of carotid web on CT angiography. Journal of NeuroInterventional Surgery. 17(7). 769–774. 1 indexed citations
8.
Liu, Jin, Lina Zhao, Hulin Kuang, et al.. (2024). A2HTL: An Automated Hybrid Transformer-Based Learning for Predicting Survival of Esophageal Cancer Using CT Images. IEEE Transactions on NanoBioscience. 23(4). 548–555. 1 indexed citations
9.
Kuang, Hulin, et al.. (2023). Automated Collateral Scoring on CT Angiography of Patients with Acute Ischemic Stroke Using Hybrid CNN and Transformer Network. Biomedicines. 11(2). 243–243. 9 indexed citations
10.
Ma, Lei, Hulin Kuang, Jin Liu, Chengchao Shen, & Jianxin Wang. (2023). Improving Medical Image Denoising via a Lightweight Plug-and-play Module. 29. 1350–1355.
11.
Kuang, Hulin, et al.. (2022). Predicting length of stay in ICU and mortality with temporal dilated separable convolution and context-aware feature fusion. Computers in Biology and Medicine. 151(Pt A). 106278–106278. 12 indexed citations
12.
Liu, Jin, Jianhong Cheng, Hulin Kuang, et al.. (2022). DARC: Deep adaptive regularized clustering for histopathological image classification. Medical Image Analysis. 80. 102521–102521. 19 indexed citations
13.
Cheng, Jianhong, et al.. (2021). Multimodal Disentangled Variational Autoencoder With Game Theoretic Interpretability for Glioma Grading. IEEE Journal of Biomedical and Health Informatics. 26(2). 673–684. 45 indexed citations
14.
Kuang, Hulin, Bijoy K. Menon, Sung‐Il Sohn, & Wu Qiu. (2021). EIS-Net: Segmenting early infarct and scoring ASPECTS simultaneously on non-contrast CT of patients with acute ischemic stroke. Medical Image Analysis. 70. 101984–101984. 51 indexed citations
15.
Qiu, Wu, Hulin Kuang, Johanna M. Ospel, et al.. (2021). Automated Prediction of Ischemic Brain Tissue Fate from Multiphase Computed Tomographic Angiography in Patients with Acute Ischemic Stroke Using Machine Learning. Journal of Stroke. 23(2). 234–243. 20 indexed citations
16.
Kuang, Hulin, Bijoy K. Menon, & Wu Qiu. (2020). Automated stroke lesion segmentation in non-contrast CT scans using dense multi-path contextual generative adversarial network. Physics in Medicine and Biology. 65(21). 215013–215013. 16 indexed citations
17.
Najm, Mohamed, Hulin Kuang, Uzair Jogiat, et al.. (2019). Automated brain extraction from head CT and CTA images using convex optimization with shape propagation. Computer Methods and Programs in Biomedicine. 176. 1–8. 28 indexed citations
18.
Kuang, Hulin, Mohamed Najm, Debabrata Chakraborty, et al.. (2018). Automated ASPECTS on Noncontrast CT Scans in Patients with Acute Ischemic Stroke Using Machine Learning. American Journal of Neuroradiology. 40(1). 33–38. 88 indexed citations
19.
Qiu, Wu, Hulin Kuang, Zarina Assis, et al.. (2018). Radiomics-Based Intracranial Thrombus Features on CT and CTA Predict Recanalization with Intravenous Alteplase in Patients with Acute Ischemic Stroke. American Journal of Neuroradiology. 40(1). 39–44. 74 indexed citations
20.
Kuang, Hulin, Leanne Lai Hang Chan, & Hong Yan. (2015). Multi-class fruit detection based on multiple color channels. 1–7. 15 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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