Zhixin Qiu

1.0k total citations
49 papers, 790 citations indexed

About

Zhixin Qiu is a scholar working on Molecular Biology, Oncology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Zhixin Qiu has authored 49 papers receiving a total of 790 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 17 papers in Oncology and 16 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Zhixin Qiu's work include Lung Cancer Treatments and Mutations (14 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and RNA modifications and cancer (6 papers). Zhixin Qiu is often cited by papers focused on Lung Cancer Treatments and Mutations (14 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and RNA modifications and cancer (6 papers). Zhixin Qiu collaborates with scholars based in China, United States and Australia. Zhixin Qiu's co-authors include Weimin Li, Shuang Zhao, Bojiang Chen, Yanqi He, Xianming Mo, Dan Liu, Kui Zhang, Yalun Li, Min Zhou and Ping Zhou and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Zhixin Qiu

44 papers receiving 784 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhixin Qiu China 20 333 216 199 147 133 49 790
Zongjuan Li China 16 384 1.2× 259 1.2× 189 0.9× 188 1.3× 182 1.4× 29 783
Chitra Joseph United Kingdom 19 390 1.2× 354 1.6× 227 1.1× 159 1.1× 262 2.0× 36 923
Siu W. Lam Netherlands 12 251 0.8× 252 1.2× 102 0.5× 150 1.0× 128 1.0× 19 753
Yiqun Zhang United States 17 288 0.9× 346 1.6× 138 0.7× 102 0.7× 143 1.1× 36 805
Luis A. Martinez United States 11 366 1.1× 423 2.0× 205 1.0× 212 1.4× 172 1.3× 17 868
Yao Xie China 13 308 0.9× 276 1.3× 103 0.5× 181 1.2× 124 0.9× 43 822
Cristina Pérez-Ramírez Spain 14 309 0.9× 211 1.0× 161 0.8× 108 0.7× 177 1.3× 50 762
Nikolaos Syrigos Greece 12 187 0.6× 279 1.3× 190 1.0× 76 0.5× 91 0.7× 61 599
Gianmaria Miolo Italy 17 423 1.3× 399 1.8× 166 0.8× 125 0.9× 196 1.5× 86 996

Countries citing papers authored by Zhixin Qiu

Since Specialization
Citations

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

Fields of papers citing papers by Zhixin Qiu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhixin Qiu

This figure shows the co-authorship network connecting the top 25 collaborators of Zhixin Qiu. A scholar is included among the top collaborators of Zhixin Qiu 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 Zhixin Qiu. Zhixin Qiu 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.
Huang, Shaoqiang, Lei Xiao, Zhongwei Zhang, et al.. (2025). Immune-cell signatures of persistent inflammation, immunosuppression, and catabolism syndrome after sepsis. Med. 6(5). 100569–100569. 9 indexed citations
3.
Wu, Fan, Peng Yuan, Yulan Zeng, et al.. (2024). 101P Circulating tumor DNA minimal residual disease predicts the risk of progression after long-term response to first-line immunotherapy in advanced NSCLC. Annals of Oncology. 35. S254–S254. 1 indexed citations
4.
Wang, Haiyan, et al.. (2023). Deep learning for predicting the risk of immune checkpoint inhibitor-related pneumonitis in lung cancer. Clinical Radiology. 78(5). e377–e385. 12 indexed citations
5.
Qiu, Zhixin, Qingxia Wu, Shuo Wang, et al.. (2022). Development of a deep learning‐based method to diagnose pulmonary ground‐glass nodules by sequential computed tomography imaging. Thoracic Cancer. 13(4). 602–612. 7 indexed citations
6.
Li, Jingwei, Qiran Zhang, Jun Shao, et al.. (2021). Artificial intelligence-assisted decision making for prognosis and drug efficacy prediction in lung cancer patients: a narrative review. Journal of Thoracic Disease. 13(12). 7021–7033. 22 indexed citations
7.
Qiu, Zhixin, Bingwei Ye, Ke Wang, et al.. (2020). Unique Genetic Characteristics and Clinical Prognosis of Female Patients with Lung Cancer Harboring RET Fusion Gene. Scientific Reports. 10(1). 10387–10387. 12 indexed citations
8.
Qiu, Zhixin, Jiasheng Liu, Tao Fan, et al.. (2020). Analysis of the clinical characteristics of 77 COVID-19 deaths. Scientific Reports. 10(1). 16384–16384. 33 indexed citations
9.
Zhang, Xin, Ji Wang, Gang Wang, et al.. (2020). Multidimensional Assessment of Asthma Identifies Clinically Relevant Phenotype Overlap: A Cross-Sectional Study. The Journal of Allergy and Clinical Immunology In Practice. 9(1). 349–362.e18. 24 indexed citations
10.
Qiu, Zhixin, Bingwei Ye, Shuang Zhao, et al.. (2019). Non‐canonical Raf‐1/p70S6K signalling in non–small‐cell lung cancer. Journal of Cellular and Molecular Medicine. 23(11). 7632–7640. 9 indexed citations
11.
12.
Qiu, Zhixin, et al.. (2016). The p70S6K Specific Inhibitor PF-4708671 Impedes Non-Small Cell Lung Cancer Growth. PLoS ONE. 11(1). e0147185–e0147185. 30 indexed citations
13.
Zhao, Shuang, Lei Li, Zhixin Qiu, et al.. (2016). [Clinical Epidemiology and Histological Characteristics of 3,663 Lung Cancer Patients in Sichuan Province from 2008 to 2013].. SHILAP Revista de lepidopterología. 19(2). 70–6. 4 indexed citations
14.
Qiu, Zhixin, Yue Cheng, Dan Liu, et al.. (2016). Clinical, pathological, and radiological characteristics of solitary ground-glass opacity lung nodules on high-resolution computed tomography. Therapeutics and Clinical Risk Management. Volume 12. 1445–1453. 24 indexed citations
15.
Liu, Dan, et al.. (2015). The Prognostic Role of mTOR and P-mTOR for Survival in Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis. PLoS ONE. 10(2). e0116771–e0116771. 25 indexed citations
16.
Chen, Bojiang, Zhi Tan, Jun Gao, et al.. (2015). Hyperphosphorylation of ribosomal protein S6 predicts unfavorable clinical survival in non-small cell lung cancer. Journal of Experimental & Clinical Cancer Research. 34(1). 126–126. 53 indexed citations
17.
Zhao, Shuang, Zhixin Qiu, Li Zhang, & Weimin Li. (2015). Prognostic values of ERK1/2 and p-ERK1/2 expressions for poor survival in non-small cell lung cancer. Tumor Biology. 36(6). 4143–4150. 17 indexed citations
18.
Chen, Bojiang, Wen Zhang, Hong Chen, et al.. (2014). Downregulation of ribosomal protein S6 inhibits the growth of non-small cell lung cancer by inducing cell cycle arrest, rather than apoptosis. Cancer Letters. 354(2). 378–389. 39 indexed citations
19.
Li, Yalun, Yanqi He, Zhixin Qiu, et al.. (2014). CRTC2 and PROM1 expression in non-small cell lung cancer: analysis by Western blot and immunohistochemistry. Tumor Biology. 35(12). 11719–11726. 5 indexed citations
20.
Qiu, Zhixin, Lei Wang, Juan Han, et al.. (2012). Prognostic impact of Raf‐1 and p‐Raf‐1 expressions for poor survival rate in non‐small cell lung cancer. Cancer Science. 103(10). 1774–1779. 13 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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