Qinghua Zhou

5.9k total citations · 1 hit paper
215 papers, 3.8k citations indexed

About

Qinghua Zhou is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Molecular Biology. According to data from OpenAlex, Qinghua Zhou has authored 215 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 95 papers in Pulmonary and Respiratory Medicine, 73 papers in Oncology and 68 papers in Molecular Biology. Recurrent topics in Qinghua Zhou's work include Lung Cancer Treatments and Mutations (58 papers), Lung Cancer Diagnosis and Treatment (41 papers) and Lung Cancer Research Studies (22 papers). Qinghua Zhou is often cited by papers focused on Lung Cancer Treatments and Mutations (58 papers), Lung Cancer Diagnosis and Treatment (41 papers) and Lung Cancer Research Studies (22 papers). Qinghua Zhou collaborates with scholars based in China, United States and United Kingdom. Qinghua Zhou's co-authors include Jun Chen, Yan Xu, Hongyu Liu, Yaguang Fan, Fu‐Dong Shi, Boning Liu, Hongyu Liu, Xiang Wu, Han‐Yu Deng and Xuebing Li and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Environmental Science & Technology.

In The Last Decade

Qinghua Zhou

197 papers receiving 3.7k citations

Hit Papers

Comparisons between the National Comprehensive Cancer Net... 2010 2026 2015 2020 2010 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qinghua Zhou China 29 1.7k 1.5k 1.2k 926 387 215 3.8k
Mauricio Burotto United States 24 1.5k 0.9× 1.9k 1.2× 1.3k 1.1× 746 0.8× 408 1.1× 101 3.7k
Nithya Ramnath United States 33 1.7k 1.0× 1.5k 1.0× 1.4k 1.2× 666 0.7× 312 0.8× 123 4.1k
Jennifer L. Spratlin Canada 24 1.2k 0.7× 2.0k 1.3× 1.4k 1.2× 767 0.8× 412 1.1× 92 3.6k
Peter J. Van Veldhuizen United States 34 1.3k 0.8× 1.4k 0.9× 1.4k 1.2× 827 0.9× 288 0.7× 96 3.6k
Cheng Zhan China 31 1.6k 1.0× 975 0.6× 1.6k 1.4× 1.0k 1.1× 302 0.8× 212 3.5k
Young‐Chul Kim South Korea 33 1.9k 1.1× 2.2k 1.4× 878 0.7× 474 0.5× 373 1.0× 241 4.1k
Andries M. Bergman Netherlands 33 1.6k 1.0× 1.8k 1.2× 1.6k 1.4× 797 0.9× 211 0.5× 158 4.5k
Quincy S. Chu Canada 34 1.6k 0.9× 2.1k 1.3× 1.3k 1.1× 576 0.6× 347 0.9× 134 4.0k
Teresa A. Goldin United States 4 1.2k 0.7× 1.9k 1.2× 2.1k 1.7× 1.3k 1.4× 338 0.9× 5 4.7k
Takeshi Ueda Japan 32 2.0k 1.2× 1.2k 0.8× 1.8k 1.5× 899 1.0× 418 1.1× 156 4.2k

Countries citing papers authored by Qinghua Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Qinghua Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qinghua Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Qinghua Zhou. A scholar is included among the top collaborators of Qinghua Zhou 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 Qinghua Zhou. Qinghua Zhou 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.
Zhai, Wei, Xiaodan Li, Tengfei Zhou, et al.. (2025). A machine learning-based 18F-FDG PET/CT multi-modality fusion radiomics model to predict Mediastinal-Hilar lymph node metastasis in NSCLC: a multi-centre study. Clinical Radiology. 83. 106832–106832. 1 indexed citations
2.
Zhang, Qianting, Yuning Feng, Zhenxing Xu, et al.. (2025). Quantitative non-volatile sensometabolome of Longjing tea and discrimination of taste quality by sensory analysis, large-scale quantitative metabolomics and machine learning. Food Chemistry. 485. 144496–144496. 3 indexed citations
4.
Zhou, Qinghua, et al.. (2024). Unified gear tribo-dynamic of transient mixed lubrication and nonlinear dynamics and its experimental validation. Mechanical Systems and Signal Processing. 223. 111860–111860. 6 indexed citations
5.
6.
Xu, Duo, Yanyun Gao, Haitang Yang, et al.. (2024). BAP1 Deficiency Inflames the Tumor Immune Microenvironment and Is a Candidate Biomarker for Immunotherapy Response in Malignant Pleural Mesothelioma. JTO Clinical and Research Reports. 5(5). 100672–100672. 5 indexed citations
8.
Zhu, Lingling, et al.. (2023). Enhancing the anti-tumor response by combining DNA damage repair inhibitors in the treatment of solid tumors. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 1878(4). 188910–188910. 10 indexed citations
9.
Jia, Xinhua, Yufei Li, Yaguang Fan, et al.. (2023). Effect of Arsenic Exposure and Cigarette Smoking on Total and Cause-Specific Mortality. Journal of Occupational and Environmental Medicine. 65(3). 217–223. 1 indexed citations
10.
Jia, Xinhua, Zheng Su, Fanghui Zhao, et al.. (2022). Synergy of arsenic with smoking in causing cardiovascular disease mortality: A cohort study with 27 follow-up years in China. Frontiers in Public Health. 10. 1012267–1012267. 2 indexed citations
11.
Zhou, Qinghua, et al.. (2022). A machine learning-based electron density (MLED) model in the inner magnetosphere. Earth and Planetary Physics. 6(0). 0–0. 5 indexed citations
12.
Yin, Liyuan, Yi Zhang, Lijuan Yin, et al.. (2021). Novel Mitochondria-Based Targeting Restores Responsiveness in Therapeutically Resistant Human Lung Cancer Cells. Molecular Cancer Therapeutics. 20(12). 2527–2538. 6 indexed citations
13.
Fan, Yaguang, Zheng Su, Liang Hao, et al.. (2021). Lung cancer risk following previous abnormal chest radiographs: A 27‐year follow‐up study of a Chinese lung screening cohort. Thoracic Cancer. 12(24). 3387–3395. 2 indexed citations
14.
Xie, Yang, Wei Lü, Shidan Wang, et al.. (2018). Validation of the 12-gene Predictive Signature for Adjuvant Chemotherapy Response in Lung Cancer. Clinical Cancer Research. 25(1). 150–157. 13 indexed citations
15.
Yang, Lin, Shidan Wang, David E. Gerber, et al.. (2018). Main bronchus location is a predictor for metastasis and prognosis in lung adenocarcinoma: A large cohort analysis. Lung Cancer. 120. 22–26. 18 indexed citations
16.
Zhang, Li, Huiyi Yang, Wenchao Liu, et al.. (2012). Detection of EGFR Somatic Mutations in Non-Small Cell Lung Cancer (NSCLC) Using a Novel Mutant-Enriched Liquidchip (MEL) Technology. Current Drug Metabolism. 13(7). 1007–1011. 11 indexed citations
17.
Nadiminty, Nagalakshmi, Wei Lou, Meng Sun, et al.. (2010). Aberrant Activation of the Androgen Receptor by NF-κB2/p52 in Prostate Cancer Cells. Cancer Research. 70(8). 3309–3319. 91 indexed citations
18.
Wu, Zhihao, et al.. (2010). Autoantibodies as the Early Diagnostic Biomarkers for Lung Cancer. SHILAP Revista de lepidopterología. 1 indexed citations
19.
Dong, Mei, Feng-yi Feng, Yang Zhang, et al.. (2008). [Phase III clinical study of zoledronic acid in the treatment of pain induced by bone metastasis from solid tumor or multiple myeloma].. PubMed. 30(3). 215–20. 4 indexed citations
20.
Li, Junwei, et al.. (2007). [Expression and their significance of ezrin and E-cadherin in non-small cell lung cancer].. PubMed. 10(3). 183–7. 2 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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