Rong Niu

913 total citations
49 papers, 667 citations indexed

About

Rong Niu is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Rong Niu has authored 49 papers receiving a total of 667 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Pulmonary and Respiratory Medicine, 19 papers in Radiology, Nuclear Medicine and Imaging and 9 papers in Molecular Biology. Recurrent topics in Rong Niu's work include Lung Cancer Diagnosis and Treatment (18 papers), Radiomics and Machine Learning in Medical Imaging (18 papers) and Medical Imaging Techniques and Applications (11 papers). Rong Niu is often cited by papers focused on Lung Cancer Diagnosis and Treatment (18 papers), Radiomics and Machine Learning in Medical Imaging (18 papers) and Medical Imaging Techniques and Applications (11 papers). Rong Niu collaborates with scholars based in China, Japan and United States. Rong Niu's co-authors include Xiaonan Shao, Xiaoliang Shao, Yuetao Wang, Zhenxing Jiang, Yoshihiko Yamazaki, Shigehiko Mizutani, Yousheng Jia, Katumi Sumikawa, Tomomitsu Okamoto and Zhenxin Zhao and has published in prestigious journals such as Nucleic Acids Research, PLoS ONE and Journal of Power Sources.

In The Last Decade

Rong Niu

46 papers receiving 661 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rong Niu China 15 226 175 147 89 52 49 667
Kevin Y. Wu Canada 16 210 0.9× 138 0.8× 190 1.3× 147 1.7× 26 0.5× 69 889
Joerg Liebmann Germany 10 281 1.2× 123 0.7× 259 1.8× 36 0.4× 130 2.5× 16 816
Yang Han China 19 383 1.7× 78 0.4× 219 1.5× 204 2.3× 39 0.8× 61 901
Daisuke Yamashita Japan 17 297 1.3× 81 0.5× 145 1.0× 148 1.7× 59 1.1× 44 886
Michael Weaver United States 11 211 0.9× 107 0.6× 99 0.7× 44 0.5× 62 1.2× 22 1.0k
Shirin Farivar Iran 11 234 1.0× 50 0.3× 272 1.9× 67 0.8× 58 1.1× 58 719
Xi Ran China 10 113 0.5× 73 0.4× 60 0.4× 34 0.4× 99 1.9× 35 415
Jiahui Chen China 17 149 0.7× 117 0.7× 121 0.8× 54 0.6× 35 0.7× 70 1.0k
Robert E. Hynds United Kingdom 19 269 1.2× 435 2.5× 41 0.3× 61 0.7× 36 0.7× 45 1.0k
Giovina Vianale Italy 17 301 1.3× 411 2.3× 85 0.6× 65 0.7× 114 2.2× 29 1.1k

Countries citing papers authored by Rong Niu

Since Specialization
Citations

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

Fields of papers citing papers by Rong Niu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rong Niu

This figure shows the co-authorship network connecting the top 25 collaborators of Rong Niu. A scholar is included among the top collaborators of Rong Niu 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 Rong Niu. Rong Niu 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.
2.
Niu, Rong, Lu Ni, & Feng Zhu. (2025). Emerging technologies and neuroscience-based approaches in dyslexia: a narrative review toward integrative and personalized solutions. Frontiers in Human Neuroscience. 19. 1683924–1683924.
3.
Niu, Rong, Jianxiong Gao, Yan Sun, et al.. (2025). New Advances in Imaging-Based Preoperative Prediction of STAS in Lung Adenocarcinoma: From CT and PET/CT to Radiomics and Deep Learning. Academic Radiology. 33(1). 281–296.
4.
Zhao, Zhenxin, Zonglin Yi, Rong Niu, et al.. (2024). Deciphering the multi-electron redox chemistry of metal-sulfide electrode toward advanced aqueous Cu ion storage. Journal of Material Science and Technology. 222. 174–181. 11 indexed citations
5.
Niu, Rong, Jie Ding, Jiajun Chen, Zhenxin Zhao, & Xiaomin Wang. (2024). Deciphering the energy storage mechanism of CoS2 nanowire arrays for High-Energy aqueous copper-ion batteries. Journal of Colloid and Interface Science. 678(Pt B). 741–749. 14 indexed citations
6.
Sun, Yan, Rong Niu, Jianxiong Gao, et al.. (2024). PET/CT radiomics and deep learning in the diagnosis of benign and malignant pulmonary nodules: progress and challenges. Frontiers in Oncology. 14. 1491762–1491762. 3 indexed citations
7.
Zhang, Zhufeng, et al.. (2024). Stroke nurse-led intravenous thrombolytic therapy strategy for ischemic stroke based on timeline process: A quality improvement program from China. International Journal of Nursing Sciences. 11(5). 521–527. 1 indexed citations
8.
Niu, Rong, Xiaoliang Shao, Xiaoliang Shao, et al.. (2023). New research progress on 18F-FDG PET/CT radiomics for EGFR mutation prediction in lung adenocarcinoma: a review. Frontiers in Oncology. 13. 1242392–1242392. 8 indexed citations
9.
Niu, Rong, et al.. (2023). Association Analysis of Maximum Standardized Uptake Values Based on 18F-FDG PET/CT and EGFR Mutation Status in Lung Adenocarcinoma. Journal of Personalized Medicine. 13(3). 396–396. 5 indexed citations
10.
Chen, Jiajun, et al.. (2023). High-Entropy Materials: Features for Lithium–Sulfur Battery Applications. Metals. 13(5). 833–833. 14 indexed citations
11.
12.
Niu, Rong, Xiaoliang Shao, Xiaoliang Shao, et al.. (2021). Maximum Standardized Uptake Value of 18F-deoxyglucose PET Imaging Increases the Effectiveness of CT Radiomics in Differentiating Benign and Malignant Pulmonary Ground-Glass Nodules. Frontiers in Oncology. 11. 727094–727094. 11 indexed citations
13.
Niu, Rong, Yuetao Wang, Xiaoliang Shao, et al.. (2021). Association Between 18F-FDG PET/CT-Based SUV Index and Malignant Status of Persistent Ground-Glass Nodules. Frontiers in Oncology. 11. 594693–594693. 1 indexed citations
14.
Li, Yuanfeng, et al.. (2021). Layout Design of Medical Terminal Interface Combining User-Oriented andGenetic Algorithm. Journal of Computer-Aided Design & Computer Graphics. 33(5). 662–670. 1 indexed citations
15.
16.
Hu, Lijun, Xiaoliang Shao, Chun Qiu, et al.. (2020). Hepatic steatosis is associated with abnormal hepatic enzymes, visceral adiposity, altered myocardial glucose uptake measured by 18F-FDG PET/CT. BMC Endocrine Disorders. 20(1). 75–75. 10 indexed citations
17.
Shao, Xiaonan, Rong Niu, Xiaoliang Shao, Zhenxing Jiang, & Yuetao Wang. (2020). Value of 18F-FDG PET/CT-based radiomics model to distinguish the growth patterns of early invasive lung adenocarcinoma manifesting as ground-glass opacity nodules. EJNMMI Research. 10(1). 80–80. 13 indexed citations
18.
Shao, Xiaonan, et al.. (2018). Application of siemens SMART neuro attenuation correction in brain PET imaging. Medicine. 97(38). e12502–e12502. 2 indexed citations
19.
Ling, Feng, Rong Niu, Hideyuki Hatakeyama, et al.. (2016). Reactive oxygen species stimulate mitochondrial allele segregation toward homoplasmy in human cells. Molecular Biology of the Cell. 27(10). 1684–1693. 15 indexed citations
20.
Niu, Rong, Minoru Yoshida, & Feng Ling. (2012). Increases in Mitochondrial DNA Content and 4977-bp Deletion upon ATM/Chk2 Checkpoint Activation in HeLa Cells. PLoS ONE. 7(7). e40572–e40572. 9 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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