Daoyu Hu

3.2k total citations · 1 hit paper
125 papers, 2.3k citations indexed

About

Daoyu Hu is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Daoyu Hu has authored 125 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Radiology, Nuclear Medicine and Imaging, 42 papers in Surgery and 28 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Daoyu Hu's work include MRI in cancer diagnosis (49 papers), Radiomics and Machine Learning in Medical Imaging (22 papers) and Advanced X-ray and CT Imaging (11 papers). Daoyu Hu is often cited by papers focused on MRI in cancer diagnosis (49 papers), Radiomics and Machine Learning in Medical Imaging (22 papers) and Advanced X-ray and CT Imaging (11 papers). Daoyu Hu collaborates with scholars based in China, United States and Hong Kong. Daoyu Hu's co-authors include Zhen Li, Wei Xia, Jianbo Shao, Yu Guo, Yaqi Shen, Xuehua Peng, Xuemei Hu, Ihab R. Kamel, John N. Morelli and Yanchun Wang and has published in prestigious journals such as Scientific Reports, Radiology and International Journal of Radiation Oncology*Biology*Physics.

In The Last Decade

Daoyu Hu

116 papers receiving 2.3k citations

Hit Papers

Clinical and CT features in pediatric patients with COVID... 2020 2026 2022 2024 2020 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Clinical and CT features in pediatric patients with COVID‐19 infection: Different points from adults
    2020 719 citations Wei Xia, Zhen Li et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daoyu Hu China 23 989 601 504 414 364 125 2.3k
Laure Fournier France 30 1.4k 1.4× 241 0.4× 598 1.2× 961 2.3× 590 1.6× 136 3.5k
Derek M. Fine United States 34 587 0.6× 1.2k 2.0× 599 1.2× 387 0.9× 109 0.3× 101 3.9k
Gianpaolo Carrafiello Italy 33 779 0.8× 305 0.5× 1.4k 2.8× 1.3k 3.2× 612 1.7× 236 3.8k
Soon Ho Yoon South Korea 32 1.7k 1.7× 907 1.5× 767 1.5× 1.3k 3.1× 859 2.4× 179 4.1k
Shalom Kalnicki United States 32 878 0.9× 384 0.6× 1.0k 2.1× 1.1k 2.6× 1.2k 3.2× 186 3.7k
Christine Hoeffel France 35 1.2k 1.2× 198 0.3× 2.0k 4.0× 737 1.8× 1.1k 3.1× 209 4.5k
Madhur Garg United States 29 568 0.6× 390 0.6× 918 1.8× 1.1k 2.6× 1.1k 3.2× 147 3.3k
Tina Lam China 14 760 0.8× 455 0.8× 76 0.2× 212 0.5× 190 0.5× 27 1.5k
Sanjay Thulkar India 33 726 0.7× 209 0.3× 1.4k 2.7× 1.5k 3.6× 1.0k 2.8× 294 3.9k
Muşturay Karçaaltıncaba Türkiye 32 788 0.8× 186 0.3× 1.6k 3.2× 841 2.0× 274 0.8× 201 3.8k

Countries citing papers authored by Daoyu Hu

Since Specialization
Citations

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

Fields of papers citing papers by Daoyu Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daoyu Hu

This figure shows the co-authorship network connecting the top 25 collaborators of Daoyu Hu. A scholar is included among the top collaborators of Daoyu Hu 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 Daoyu Hu. Daoyu Hu 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.
Liang, Siyuan, Daoyu Hu, Zhihua Zhang, et al.. (2025). Research on Electromagnetic Harmonic Composition and Loss Characteristics of High Temperature Superconducting Magnet in EDS System. IEEE Transactions on Applied Superconductivity. 35(7). 1–12.
2.
Chen, Jun, Yufan Wang, Xuemei Hu, et al.. (2024). Optimizing CT Esophagography: Ex Vivo Study on Contrast Ratios, Image Quality, and Dual-Energy Benefits. Bioengineering. 11(12). 1300–1300. 2 indexed citations
3.
Zhang, Yong, Daoyu Hu, Wei Li, et al.. (2023). 2V-CBCT: Two-Orthogonal-Projection Based CBCT Reconstruction and Dose Calculation from Real CBCT Projection Data. International Journal of Radiation Oncology*Biology*Physics. 117(2). e748–e748. 1 indexed citations
4.
Li, Yuanqiu, Jun Chen, Yaqi Shen, et al.. (2023). Enhancing the Differentiation between Intestinal Behçet’s Disease and Crohn’s Disease through Quantitative Computed Tomography Analysis. Bioengineering. 10(10). 1211–1211. 2 indexed citations
5.
Li, Shichao, Ping Liang, Jiali Li, et al.. (2022). Noninvasive assessment of renal function and fibrosis in CKD patients using histogram analysis based on diffusion kurtosis imaging. Japanese Journal of Radiology. 41(2). 180–193. 7 indexed citations
6.
Liang, Ping, et al.. (2022). Noninvasive assessment of clinical and pathological characteristics of patients with IgA nephropathy by diffusion kurtosis imaging. Insights into Imaging. 13(1). 18–18. 7 indexed citations
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Lu, Jingyu, Hao Yu, Zhen Li, et al.. (2019). Apparent diffusion coefficient-based histogram analysis differentiates histological subtypes of periampullary adenocarcinoma. World Journal of Gastroenterology. 25(40). 6116–6128. 7 indexed citations
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Xia, Wei, et al.. (2017). Different information by MRI compare to ultrasound in fetal intracranial space occupying lesions. Child s Nervous System. 33(12). 2129–2136. 4 indexed citations
13.
Meng, Xiaoyan, Xiaohong Chen, Yaqi Shen, et al.. (2016). Proton-density fat fraction measurement: A viable quantitative biomarker for differentiating adrenal adenomas from nonadenomas. European Journal of Radiology. 86. 112–118. 7 indexed citations
14.
Hu, Shan, Daoyu Hu, Wenzhen Zhu, Liang Wang, & Zi Wang. (2016). Tuberous sclerosis complex: Imaging characteristics in 11 cases and review of the literature. Journal of Huazhong University of Science and Technology [Medical Sciences]. 36(4). 601–606. 2 indexed citations
15.
Min, Xiangde, Liang Wang, Liang Li, et al.. (2015). Prostate cancer: the correlation between apparent diffusion coefficient values obtained from high resolution diffusion-weighted imaging and Gleason scores. Zhonghua fangshexian yixue zazhi. 49(3). 191–194. 2 indexed citations
16.
Hu, Xuemei, Liya Ma, Jinhua Zhang, et al.. (2014). Study of CT pulmonary angiography technique in pulmonary embolism-low dose and low concentration. Zhonghua fangshexian yixue zazhi. 48(10). 811–815.
17.
Tang, Hao, Zi Wang, Liang Wang, et al.. (2014). Depiction of Transplant Renal Vascular Anatomy and Complications: Unenhanced MR Angiography by Using Spatial Labeling with Multiple Inversion Pulses. Radiology. 271(3). 879–887. 23 indexed citations
18.
Hu, Daoyu, et al.. (2013). Role of diffusion-weighted imaging in early ankylosing spondylitis. Chinese Medical Journal. 126(4). 668–673. 4 indexed citations
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20.
Hu, Daoyu, et al.. (2005). Computed Tomographic Qualitative Diagnosis of Renal Masses. The Chinese-German Journal of Clinical Oncology. 4(6). 369–372.

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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