Min Xu

3.7k total citations
135 papers, 2.6k citations indexed

About

Min Xu is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Min Xu has authored 135 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Pulmonary and Respiratory Medicine, 32 papers in Radiology, Nuclear Medicine and Imaging and 29 papers in Molecular Biology. Recurrent topics in Min Xu's work include Radiomics and Machine Learning in Medical Imaging (21 papers), Hepatocellular Carcinoma Treatment and Prognosis (12 papers) and Medical Imaging Techniques and Applications (10 papers). Min Xu is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (21 papers), Hepatocellular Carcinoma Treatment and Prognosis (12 papers) and Medical Imaging Techniques and Applications (10 papers). Min Xu collaborates with scholars based in China, Hong Kong and Japan. Min Xu's co-authors include Jiansong Ji, Zhongwei Zhao, Qiaoyou Weng, Chenying Lu, Dengke Zhang, Jiansong Ji, Bin Deng, Minjiang Chen, Qi Chen and Jingjing Song and has published in prestigious journals such as SHILAP Revista de lepidopterología, Free Radical Biology and Medicine and Nanoscale.

In The Last Decade

Min Xu

123 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Min Xu China 29 767 706 517 451 366 135 2.6k
Liang Wang China 27 1.1k 1.5× 626 0.9× 267 0.5× 245 0.5× 521 1.4× 129 2.3k
Hui Yan China 28 970 1.3× 263 0.4× 215 0.4× 336 0.7× 413 1.1× 129 2.4k
Per Borgström United States 28 1.0k 1.4× 361 0.5× 216 0.4× 565 1.3× 412 1.1× 75 2.8k
Hong Zhao China 31 1.5k 2.0× 598 0.8× 154 0.3× 1.1k 2.4× 460 1.3× 148 3.3k
Yi Luo China 32 1.8k 2.4× 660 0.9× 203 0.4× 854 1.9× 756 2.1× 149 4.3k
Shuai Zhang China 30 1.3k 1.7× 330 0.5× 249 0.5× 491 1.1× 830 2.3× 183 2.7k
Philip M. Carpenter United States 26 1.3k 1.6× 495 0.7× 482 0.9× 652 1.4× 673 1.8× 73 3.3k
Florian Blaschke Germany 31 1.0k 1.4× 431 0.6× 401 0.8× 216 0.5× 324 0.9× 108 3.4k

Countries citing papers authored by Min Xu

Since Specialization
Citations

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

Fields of papers citing papers by Min Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Min Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Min Xu. A scholar is included among the top collaborators of Min Xu 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 Min Xu. Min Xu 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.
Xia, Zhinan, Yu Dong, Xinyu Hao, et al.. (2025). The positive feedback loop between SP1 and MAP2K2 significantly drives resistance to VEGFR inhibitors in clear cell renal cell carcinoma. International Journal of Biological Sciences. 21(2). 860–873. 3 indexed citations
2.
Pan, Xiaotian, et al.. (2025). Comparison of microbiota in different intestinal regions between hibernating and active Daurian ground squirrels. The European Zoological Journal. 92(1). 1571–1588.
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5.
Xu, Min, Mengjie Qiu, Yi Zhou, et al.. (2024). Solamargine improves the therapeutic efficacy of anti-PD-L1 in lung adenocarcinoma by inhibiting STAT1 activation. Phytomedicine. 128. 155538–155538. 4 indexed citations
6.
Zhang, Ke, Wenbo Wang, Min Xu, et al.. (2024). ViT‐based quantification of intratumoral heterogeneity for predicting the early recurrence in HCC following multiple ablation. Liver International. 45(4). e16051–e16051. 2 indexed citations
7.
Zhang, Yuan, et al.. (2023). Clinical Application of Dark-blood Imaging in Head and Neck CT Angiography: Effect on Image Quality and Plaque Visibility. Academic Radiology. 31(6). 2478–2487. 3 indexed citations
8.
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Chen, Weiyue, Chunli Kong, Minjiang Chen, et al.. (2023). Non-invasive prediction model of axillary lymph node status in patients with early-stage breast cancer: a feasibility study based on dynamic contrast-enhanced-MRI radiomics. British Journal of Radiology. 97(1154). 439–450. 8 indexed citations
10.
Liu, Siyu, Li‐Yang Sun, Lan‐Qing Yao, et al.. (2022). Diagnostic Performance of AFP, AFP-L3, or PIVKA-II for Hepatitis C Virus-Associated Hepatocellular Carcinoma: A Multicenter Analysis. Journal of Clinical Medicine. 11(17). 5075–5075. 23 indexed citations
11.
Liu, Xinhua, Rongfang Qiu, Min Xu, et al.. (2021). KMT2C is a potential biomarker of prognosis and chemotherapy sensitivity in breast cancer. Breast Cancer Research and Treatment. 189(2). 347–361. 18 indexed citations
12.
Chen, Minjiang, Xiaoling Xu, Gaofeng Shu, et al.. (2021). Multifunctional Microspheres Dual-Loaded with Doxorubicin and Sodium Bicarbonate Nanoparticles to Introduce Synergistic Trimodal Interventional Therapy. ACS Applied Bio Materials. 4(4). 3476–3489. 11 indexed citations
13.
Gu, Jionghui, Tong Tong, Chang He, et al.. (2021). Deep learning radiomics of ultrasonography can predict response to neoadjuvant chemotherapy in breast cancer at an early stage of treatment: a prospective study. European Radiology. 32(3). 2099–2109. 90 indexed citations
14.
Tang, Bufu, Jinyu Zhu, Shiji Fang, et al.. (2021). Pharmacological inhibition of MELK restricts ferroptosis and the inflammatory response in colitis and colitis-propelled carcinogenesis. Free Radical Biology and Medicine. 172. 312–329. 69 indexed citations
15.
Xu, Min, et al.. (2020). A Nomogram for the Prognosis of Nasopharyngeal Carcinoma with MR Imaging-Detected Tumor Residue at the End of Intensity-Modulated Radiotherapy. SHILAP Revista de lepidopterología. 1 indexed citations
16.
Wang, Hailin, Qiaoyou Weng, Shiji Fang, et al.. (2019). Value of TSCT Features for Differentiating Preinvasive and Minimally Invasive Adenocarcinoma From Invasive Adenocarcinoma Presenting as Subsolid Nodules Smaller Than 3 cm. Academic Radiology. 27(3). 395–403. 6 indexed citations
17.
Xu, Min, et al.. (2017). Areas of breast tissue covered in cone beam breast CT imaging. Experimental and Therapeutic Medicine. 13(3). 913–916. 3 indexed citations
18.
Xu, Min, et al.. (2012). The influence of delineating criteria training on the delineation of tumor bed and whole breast target after breast-conserving surgery. Zhonghua fangshe zhongliuxue zazhi. 21(6). 534–538. 1 indexed citations
19.
Xu, Min, et al.. (2009). Adjuvant Phytotherapy in the Treatment of Cervical Cancer: A Systematic Review and Meta-Analysis. The Journal of Alternative and Complementary Medicine. 15(12). 1347–1353. 3 indexed citations
20.
Durairajan, Siva Sundara Kumar, et al.. (2008). Efficacy and Safety of Acupuncture for Idiopathic Parkinson's Disease: A Systematic Review. The Journal of Alternative and Complementary Medicine. 14(6). 663–671. 58 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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