Pan Huang

2.6k total citations · 1 hit paper
80 papers, 1.7k citations indexed

About

Pan Huang is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Physiology. According to data from OpenAlex, Pan Huang has authored 80 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Artificial Intelligence, 22 papers in Radiology, Nuclear Medicine and Imaging and 15 papers in Physiology. Recurrent topics in Pan Huang's work include AI in cancer detection (19 papers), Radiomics and Machine Learning in Medical Imaging (18 papers) and Nutrition and Health in Aging (6 papers). Pan Huang is often cited by papers focused on AI in cancer detection (19 papers), Radiomics and Machine Learning in Medical Imaging (18 papers) and Nutrition and Health in Aging (6 papers). Pan Huang collaborates with scholars based in China, Italy and United States. Pan Huang's co-authors include Jianghua Zhou, Antonella Santone, Francesco Mercaldo, Jiang Wang, Sukun Tian, Xiaoli Zhou, Peng Feng, Yongxue Yang, Xiaoheng Tan and Jiping Li and has published in prestigious journals such as International Journal of Molecular Sciences, IEEE Access and IEEE Transactions on Medical Imaging.

In The Last Decade

Pan Huang

75 papers receiving 1.7k citations

Hit Papers

Heterogeneity and plasticity of epithelial–mesenchymal tr... 2023 2026 2024 2025 2023 25 50 75

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pan Huang China 26 324 268 257 253 242 80 1.7k
Chung‐Chih Lin Taiwan 25 217 0.7× 602 2.2× 133 0.5× 212 0.8× 110 0.5× 97 2.1k
Shu-Fang Chen Taiwan 22 121 0.4× 261 1.0× 106 0.4× 224 0.9× 67 0.3× 95 1.8k
Alberto Malovini Italy 28 293 0.9× 634 2.4× 75 0.3× 129 0.5× 99 0.4× 101 2.1k
Ge Liu China 27 92 0.3× 540 2.0× 220 0.9× 349 1.4× 189 0.8× 115 2.3k
Francis Sahngun Nahm South Korea 22 340 1.0× 349 1.3× 199 0.8× 211 0.8× 56 0.2× 99 2.3k
Elad Maor Israel 32 218 0.7× 218 0.8× 440 1.7× 452 1.8× 50 0.2× 172 3.4k
Chulho Kim South Korea 28 214 0.7× 246 0.9× 151 0.6× 505 2.0× 85 0.4× 195 2.3k
A. H. Zwinderman Netherlands 29 444 1.4× 172 0.6× 119 0.5× 285 1.1× 76 0.3× 65 3.3k
Sang Hyun Cho South Korea 27 340 1.0× 232 0.9× 74 0.3× 328 1.3× 40 0.2× 169 2.7k
Jianning Li China 21 99 0.3× 304 1.1× 203 0.8× 195 0.8× 180 0.7× 97 1.5k

Countries citing papers authored by Pan Huang

Since Specialization
Citations

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

Fields of papers citing papers by Pan Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pan Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Pan Huang. A scholar is included among the top collaborators of Pan Huang 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 Pan Huang. Pan Huang 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.
Tian, Sukun, et al.. (2024). RADDA-Net: Residual attention-based dual discriminator adversarial network for surface defect detection. Engineering Applications of Artificial Intelligence. 136. 108887–108887. 6 indexed citations
2.
Huang, Pan, Peng He, Yi‐Fang Ping, et al.. (2024). MamlFormer: Priori-experience guiding transformer network via manifold adversarial multi-modal learning for laryngeal histopathological grading. Information Fusion. 108. 102333–102333. 19 indexed citations
3.
Lai, Chao‐Sung, Qingwen Zeng, Pan Huang, et al.. (2024). Screening of gastric cancer diagnostic biomarkers in the homologous recombination signaling pathway and assessment of their clinical and radiomic correlations. Cancer Medicine. 13(16). e70153–e70153. 3 indexed citations
5.
Huang, Pan, Qiang Ma, Lianhua Zhao, et al.. (2024). Prediction of PD-L1 tumor positive score in lung squamous cell carcinoma with H&E staining images and deep learning. Frontiers in Artificial Intelligence. 7. 1452563–1452563.
6.
He, Hai, et al.. (2024). Isolation forest-voting fusion-multioutput: A stroke risk classification method based on the multidimensional output of abnormal sample detection. Computer Methods and Programs in Biomedicine. 253. 108255–108255. 11 indexed citations
7.
Li, Tong, et al.. (2024). A bidirectional broadband multifunctional terahertz device based on vanadium dioxide. Infrared Physics & Technology. 141. 105465–105465. 1 indexed citations
9.
Song, Jingjing, Wentao Zhao, Pan Huang, et al.. (2023). Artificial intelligence applicated in gastric cancer: A bibliometric and visual analysis via CiteSpace. Frontiers in Oncology. 12. 1075974–1075974. 14 indexed citations
10.
Yang, Xing, et al.. (2022). E-TBNet: Light Deep Neural Network for Automatic Detection of Tuberculosis with X-ray DR Imaging. Sensors. 22(3). 821–821. 22 indexed citations
11.
Tian, Sukun, Pan Huang, Haifeng Ma, et al.. (2022). CASDD: Automatic Surface Defect Detection Using a Complementary Adversarial Network. IEEE Sensors Journal. 22(20). 19583–19595. 32 indexed citations
12.
Zhou, Xiaoli, et al.. (2022). ASI-DBNet: An Adaptive Sparse Interactive ResNet-Vision Transformer Dual-Branch Network for the Grading of Brain Cancer Histopathological Images. Interdisciplinary Sciences Computational Life Sciences. 15(1). 15–31. 34 indexed citations
13.
Huang, Pan, Xiaoli Zhou, Peng He, et al.. (2022). Interpretable laryngeal tumor grading of histopathological images via depth domain adaptive network with integration gradient CAM and priori experience-guided attention. Computers in Biology and Medicine. 154. 106447–106447. 21 indexed citations
14.
Zhou, Xiaoli, et al.. (2021). LPCANet: Classification of Laryngeal Cancer Histopathological Images Using a CNN with Position Attention and Channel Attention Mechanisms. Interdisciplinary Sciences Computational Life Sciences. 13(4). 666–682. 39 indexed citations
15.
Huang, Pan, Xiaoheng Tan, Xiaoli Zhou, et al.. (2021). FABNet: Fusion Attention Block and Transfer Learning for Laryngeal Cancer Tumor Grading in P63 IHC Histopathology Images. IEEE Journal of Biomedical and Health Informatics. 26(4). 1696–1707. 46 indexed citations
16.
Luo, Yilin, et al.. (2020). A quadruple protection procedure for resuming pig production in small-scale ASFV-positive farms in China. Current Research in Microbial Sciences. 2. 100014–100014. 7 indexed citations
17.
Pan, Xiaoting, Yuanjie Liu, Pan Huang, et al.. (2020). A clinical study of traditional Chinese medicine prolonging the survival of advanced gastric cancer patients by regulating the immunosuppressive cell population. Medicine. 99(16). e19757–e19757. 28 indexed citations
18.
Jiang, Chao, Xingang Yao, Jianmin Wu, et al.. (2020). Comparative review of respiratory diseases caused by coronaviruses and influenza A viruses during epidemic season. Microbes and Infection. 22(6-7). 236–244. 60 indexed citations
19.
Zhou, Jianghua, Jiang Wang, Yanjiao Shen, et al.. (2018). The association between telomere length and frailty: A systematic review and meta-analysis. Experimental Gerontology. 106. 16–20. 17 indexed citations
20.
Huang, Pan. (2013). Current Status and Development Trend of Commonly Used Techniques for Preparing Infrared Absorption Coating on Copper Substrate. Cailiao baohu. 1 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026