Le‐Qun Li

1.2k total citations
39 papers, 770 citations indexed

About

Le‐Qun Li is a scholar working on Epidemiology, Hepatology and Oncology. According to data from OpenAlex, Le‐Qun Li has authored 39 papers receiving a total of 770 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Epidemiology, 23 papers in Hepatology and 12 papers in Oncology. Recurrent topics in Le‐Qun Li's work include Liver Disease Diagnosis and Treatment (21 papers), Hepatocellular Carcinoma Treatment and Prognosis (18 papers) and Hepatitis B Virus Studies (11 papers). Le‐Qun Li is often cited by papers focused on Liver Disease Diagnosis and Treatment (21 papers), Hepatocellular Carcinoma Treatment and Prognosis (18 papers) and Hepatitis B Virus Studies (11 papers). Le‐Qun Li collaborates with scholars based in China, United States and Singapore. Le‐Qun Li's co-authors include Bang‐De Xiang, Jiazhou Ye, Yue Wang, Yuheng Li, Rongyun Mai, Feixiang Wu, Tao Bai, Tao Peng, Lu‐Nan Qi and Guobin Wu and has published in prestigious journals such as PLoS ONE, Scientific Reports and Journal of Hepatology.

In The Last Decade

Le‐Qun Li

37 papers receiving 761 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Le‐Qun Li China 16 313 310 173 150 129 39 770
Mei Guan China 16 36 0.1× 61 0.2× 234 1.4× 165 1.1× 246 1.9× 61 725
Yu-Chao Wang Taiwan 13 68 0.2× 115 0.4× 79 0.5× 94 0.6× 60 0.5× 34 380
Xu Zhu China 18 144 0.5× 469 1.5× 246 1.4× 257 1.7× 121 0.9× 75 876
Sha Lin China 14 181 0.6× 138 0.4× 70 0.4× 49 0.3× 159 1.2× 32 516
Shaoming Chen China 13 58 0.2× 15 0.0× 111 0.6× 134 0.9× 145 1.1× 48 576
Guangbing Li China 13 96 0.3× 100 0.3× 73 0.4× 95 0.6× 223 1.7× 32 496
Lu Ao China 19 57 0.2× 41 0.1× 217 1.3× 62 0.4× 424 3.3× 56 878
Lu‐Nan Qi China 12 172 0.5× 287 0.9× 284 1.6× 124 0.8× 178 1.4× 41 742
Shu Cheng China 14 129 0.4× 246 0.8× 61 0.4× 119 0.8× 228 1.8× 35 702
Emna Chelbi Tunisia 10 467 1.5× 323 1.0× 62 0.4× 94 0.6× 90 0.7× 49 708

Countries citing papers authored by Le‐Qun Li

Since Specialization
Citations

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

Fields of papers citing papers by Le‐Qun Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Le‐Qun Li. 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 Le‐Qun Li. The network helps show where Le‐Qun Li may publish in the future.

Co-authorship network of co-authors of Le‐Qun Li

This figure shows the co-authorship network connecting the top 25 collaborators of Le‐Qun Li. A scholar is included among the top collaborators of Le‐Qun Li 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 Le‐Qun Li. Le‐Qun Li 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.
Huang, Hongyang, Dandan Zeng, Rong Liang, et al.. (2025). Postoperative Adjuvant Transcatheterarterial Chemoembolization Should Be Considered Selectively for Patients with Cytokeratin-19 Positive Hepatocellular Carcinoma. Journal of Hepatocellular Carcinoma. Volume 12. 2407–2419.
2.
3.
Mai, Rongyun, Tao Bai, Rong Liang, et al.. (2020). Artificial neural network model for preoperative prediction of severe liver failure after hemihepatectomy in patients with hepatocellular carcinoma. Surgery. 168(4). 643–652. 42 indexed citations
4.
Mai, Rongyun, Jie Zeng, Rong Liang, et al.. (2020). <p>Artificial Neural Network Model for Liver Cirrhosis Diagnosis in Patients with Hepatitis B Virus-Related Hepatocellular Carcinoma</p>. Therapeutics and Clinical Risk Management. Volume 16. 639–649. 9 indexed citations
5.
Han, Chuangye, Tingdong Yu, Wei Qin, et al.. (2020). Genome-wide association study of the TP53 R249S mutation in hepatocellular carcinoma with aflatoxin B1 exposure and infection with hepatitis B virus. Journal of Gastrointestinal Oncology. 11(6). 1333–1349. 18 indexed citations
6.
7.
Wei, Meng, et al.. (2019). Clinical applicaton of three-dimensional visualization technology in hepatectomy of complex hepatocellular carcinoma. Zhonghua gan-dan waike zazhi. 25(9). 653–655. 1 indexed citations
8.
Xu, Qingguo, Shengxian Yuan, Qi-fei Tao, et al.. (2019). A novel HBx genotype serves as a preoperative predictor and fails to activate the JAK1/STATs pathway in hepatocellular carcinoma. Journal of Hepatology. 70(5). 904–917. 20 indexed citations
9.
Liao, Ying‐Yang, Rongrong Jia, Jing Cui, et al.. (2019). Serum Prealbumin is Negatively Associated with Survival in Hepatocellular Carcinoma Patients after Hepatic Resection. Journal of Cancer. 10(13). 3006–3011. 13 indexed citations
10.
Ye, Jiazhou, Rong Liang, Tao Bai, et al.. (2018). RBM38 plays a tumor-suppressor role via stabilizing the p53-mdm2 loop function in hepatocellular carcinoma. Journal of Experimental & Clinical Cancer Research. 37(1). 212–212. 46 indexed citations
11.
Zhang, Yumei, Shao‐Liang Zhu, Peng Wang, et al.. (2018). A novel, non-invasive model for diagnosing liver fibrosis stage in patients with hepatocellular carcinoma. Scientific Reports. 8(1). 13074–13074. 11 indexed citations
12.
Wang, Xiaobo, Jie Chen, Bang‐De Xiang, Feixiang Wu, & Le‐Qun Li. (2018). High CONUT score predicts poor survival and postoperative HBV reactivation in HBV-related hepatocellular carcinoma patients with low HBV-DNA levels. European Journal of Surgical Oncology. 45(5). 782–787. 22 indexed citations
13.
Gong, Wen‐Feng, et al.. (2016). Influence of preoperative antiviral therapy on HBV reactivation and liver function after liver resection in HBV-DNA-negative hepatocellular carcinoma patients. 43(15). 673. 1 indexed citations
14.
15.
Zhu, Shao‐Liang, Yun Zhao, Xueying Hu, et al.. (2016). Genetic polymorphisms -137 (rs187238) and -607 (rs1946518) in the interleukin-18 promoter may not be associated with development of hepatocellular carcinoma. Scientific Reports. 6(1). 39404–39404. 15 indexed citations
16.
Zhang, Yumei, Yongqiang Li, Zhihui Liu, et al.. (2014). Clinical Efficacy of Bevacizumab Concomitant with Pemetrexed in Patients with Advanced Non-small Cell Lung Cancer. Asian Pacific Journal of Cancer Prevention. 15(8). 3447–3450. 3 indexed citations
17.
Qi, Lu‐Nan, Tao Bai, Feixiang Wu, et al.. (2014). The p53 mutation spectrum in hepatocellular carcinoma from Guangxi, China : role of chronic hepatitis B virus infection and aflatoxin B1 exposure. Liver International. 35(3). 999–1009. 70 indexed citations
18.
Qi, Lu‐Nan, Le‐Qun Li, Yuanyuan Chen, et al.. (2013). Genome-Wide and Differential Proteomic Analysis of Hepatitis B Virus and Aflatoxin B1 Related Hepatocellular Carcinoma in Guangxi, China. PLoS ONE. 8(12). e83465–e83465. 35 indexed citations
19.
Li, Le‐Qun. (2011). Postoperative adjuvant adoptive immunotherapy for hepatocellular carcinoma:A Meta-analysis. Zhonghua zhongliu fangzhi zazhi. 1 indexed citations
20.
Chen, Defeng, et al.. (2009). Evaluation the affect of psychological counseling intervention on the immune function in the preoperative anxiety patients with liver cancer. Zhonghua xiandai huli zazhi. 15(24). 2360–2364. 1 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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