Ying Sun

28.4k total citations · 6 hit papers
404 papers, 15.0k citations indexed

About

Ying Sun is a scholar working on Otorhinolaryngology, Surgery and Oncology. According to data from OpenAlex, Ying Sun has authored 404 papers receiving a total of 15.0k indexed citations (citations by other indexed papers that have themselves been cited), including 238 papers in Otorhinolaryngology, 141 papers in Surgery and 124 papers in Oncology. Recurrent topics in Ying Sun's work include Head and Neck Cancer Studies (237 papers), Head and Neck Surgical Oncology (88 papers) and Lung Cancer Treatments and Mutations (57 papers). Ying Sun is often cited by papers focused on Head and Neck Cancer Studies (237 papers), Head and Neck Surgical Oncology (88 papers) and Lung Cancer Treatments and Mutations (57 papers). Ying Sun collaborates with scholars based in China, United States and Singapore. Ying Sun's co-authors include Jun Ma, Yu‐Pei Chen, Ling‐Long Tang, Yan‐Ping Mao, Lei Chen, Quynh‐Thu Le, Anthony T.�C. Chan, Pierre Blanchard, Guan‐Qun Zhou and Ai-Hua Lin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Lancet and Journal of Biological Chemistry.

In The Last Decade

Ying Sun

387 papers receiving 14.9k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Nasopharyngeal carcinoma

2019 2.0k citations Yu‐Pei Chen, Ying Sun et al. profile →
How Does Intensity-Modulated Radiotherapy Versus Conventional Two-Dimensional Radiotherapy Influence the Treatment Results in Nasopharyngeal Carcinoma Patients?

2010 530 citations Lei Chen, Lizhi Liu et al. profile →
Comparative safety of immune checkpoint inhibitors in cancer: systematic review and network meta-analysis

2018 416 citations Cheng Xu, Yu‐Pei Chen et al. profile →
Prognostic Value of Deep Learning PET/CT-Based Radiomics: Potential Role for Future Individual Induction Chemotherapy in Advanced Nasopharyngeal Carcinoma

2019 241 citations Hao Peng, Di Dong et al. Clinical Cancer Research profile →
Intensity-modulated radiotherapy prolongs the survival of patients with nasopharyngeal carcinoma compared with conventional two-dimensional radiotherapy: A 10-year experience with a large cohort and long follow-up

2015 240 citations Ying Sun, Jun Ma et al. profile →
Deep Learning for Automated Contouring of Primary Tumor Volumes by MRI for Nasopharyngeal Carcinoma

2019 237 citations Li Lin, Guan‐Qun Zhou et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Ying Sun	6.7k	5.4k	4.1k	3.7k	3.6k	404	15.0k
David Raben	5.2k 0.8×	6.8k 1.3×	3.7k 0.9×	5.6k 1.5×	4.4k 1.2×	236	15.2k
Christine H. Chung	7.2k 1.1×	5.6k 1.1×	4.5k 1.1×	3.6k 1.0×	4.7k 1.3×	255	15.6k
Ezra E.W. Cohen	4.7k 0.7×	8.5k 1.6×	3.2k 0.8×	5.6k 1.5×	4.7k 1.3×	421	16.9k
Paul M. Harari	5.9k 0.9×	8.6k 1.6×	4.0k 1.0×	7.2k 1.9×	4.7k 1.3×	303	18.1k
Anthony T.�C. Chan	10.2k 1.5×	11.7k 2.2×	7.2k 1.8×	5.6k 1.5×	7.8k 2.2×	456	27.6k
Barbara Burtness	5.0k 0.7×	8.5k 1.6×	3.7k 0.9×	5.0k 1.3×	4.4k 1.2×	363	16.0k
Quynh‐Thu Le	7.4k 1.1×	7.8k 1.5×	5.8k 1.4×	7.0k 1.9×	6.7k 1.9×	461	25.4k
William E. Gooding	2.3k 0.3×	7.4k 1.4×	3.1k 0.8×	4.3k 1.2×	5.0k 1.4×	283	17.2k
Nadeem Riaz	1.8k 0.3×	4.6k 0.9×	1.6k 0.4×	2.4k 0.7×	2.4k 0.7×	243	9.2k
William H. Westra	16.4k 2.5×	9.8k 1.8×	10.9k 2.7×	4.8k 1.3×	8.1k 2.3×	224	29.2k

Countries citing papers authored by Ying Sun

Since Specialization

Citations

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

Fields of papers citing papers by Ying Sun

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ying Sun

This figure shows the co-authorship network connecting the top 25 collaborators of Ying Sun. A scholar is included among the top collaborators of Ying Sun 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 Ying Sun. Ying Sun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Huang, Chien‐Yu, Chong‐You Chen, Ying Sun, et al.. (2025). Environmental Exposure to Bisphenol A Enhances Invasiveness in Papillary Thyroid Cancer. International Journal of Molecular Sciences. 26(2). 814–814. 5 indexed citations

Chen, Zihang, Xu Han, Li Lin, et al.. (2025). Harnessing deep learning to optimize induction chemotherapy choices in nasopharyngeal carcinoma. Radiotherapy and Oncology. 211. 111047–111047.

Ren, Chuan-Xian, et al.. (2024). Domain knowledge-driven encoder–decoder for nasopharyngeal carcinoma segmentation. Expert Systems with Applications. 258. 125208–125208.

Lin, Guoyu, et al.. (2024). Semi-supervised model based on implicit neural representation and mutual learning (SIMN) for multi-center nasopharyngeal carcinoma segmentation on MRI. Computers in Biology and Medicine. 175. 108368–108368. 3 indexed citations

Li, Lin, et al.. (2024). From data to decisions: Big data and AI are shaping the future of radiotherapy and individualized treatment of nasopharyngeal carcinoma. 1(1). 52–60. 1 indexed citations

Sun, Ying, Rui Li, Zhou Songyang, et al.. (2023). A Comprehensive Pan-Cancer Analysis of the Potential Biological Functions and Prognosis Values of RICTOR. Genes. 14(6). 1280–1280. 2 indexed citations

Kou, Jia, Lin Li, Guan‐Qun Zhou, et al.. (2021). Individualized elective irradiation of the clinically node‐negative neck in definitive radiotherapy for head and neck squamous cell carcinoma. Cancer Communications. 41(4). 303–315. 4 indexed citations

Chen, Zihang, et al.. (2021). Artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine. Cancer Communications. 41(11). 1100–1115. 147 indexed citations

Chen, Yue, Tianqi Luo, Si‐Si Xu, et al.. (2021). An immune‐related seven‐lncRNA signature for head and neck squamous cell carcinoma. Cancer Medicine. 10(7). 2268–2285. 15 indexed citations

10.

Mao, Yan‐Ping, Shunxin Wang, William M. Lydiatt, et al.. (2021). Unambiguous advanced radiologic extranodal extension determined by MRI predicts worse outcomes in nasopharyngeal carcinoma: Potential improvement for future editions of N category systems. Radiotherapy and Oncology. 157. 114–121. 41 indexed citations

11.

Zheng, Zi‐Qi, Zhi‐Xuan Li, Xu Liu, et al.. (2020). Long Noncoding RNA TINCR-Mediated Regulation of Acetyl-CoA Metabolism Promotes Nasopharyngeal Carcinoma Progression and Chemoresistance. Cancer Research. 80(23). 5174–5188. 86 indexed citations

12.

Chen, Yue, Zhiyong Li, Guan‐Qun Zhou, & Ying Sun. (2020). An Immune-Related Gene Prognostic Index for Head and Neck Squamous Cell Carcinoma. Clinical Cancer Research. 27(1). 330–341. 183 indexed citations

13.

Sun, Ying, et al.. (2020). Prognostic value of cystatin C in patients with acute coronary syndrome: A systematic review and meta‐analysis. European Journal of Clinical Investigation. 51(3). e13440–e13440. 10 indexed citations

14.

Peng, Hao, Di Dong, Lu Li, et al.. (2019). Prognostic Value of Deep Learning PET/CT-Based Radiomics: Potential Role for Future Individual Induction Chemotherapy in Advanced Nasopharyngeal Carcinoma. Clinical Cancer Research. 25(14). 4271–4279. 241 indexed citations breakdown →

15.

Li, Ying-Qin, Xiao-Jing Yang, Xiaojing Du, et al.. (2018). RAB37 Hypermethylation Regulates Metastasis and Resistance to Docetaxel-Based Induction Chemotherapy in Nasopharyngeal Carcinoma. Clinical Cancer Research. 24(24). 6495–6508. 24 indexed citations

16.

Zhang, Jiän, Ying-Qin Li, Rui Guo, et al.. (2018). Hypermethylation of SHISA3 Promotes Nasopharyngeal Carcinoma Metastasis by Reducing SGSM1 Stability. Cancer Research. 79(4). 747–759. 35 indexed citations

17.

Peng, Liang, Cheng Xu, Yu‐Pei Chen, et al.. (2018). Optimizing the cumulative cisplatin dose during radiotherapy in nasopharyngeal carcinoma: Dose-effect analysis for a large cohort. Oral Oncology. 89. 102–106. 15 indexed citations

18.

Ren, Xianyue, Guan‐Qun Zhou, Wei Jiang, et al.. (2015). Low SFRP1 Expression Correlates with Poor Prognosis and Promotes Cell Invasion by Activating the Wnt/β-Catenin Signaling Pathway in NPC. Cancer Prevention Research. 8(10). 968–977. 30 indexed citations

19.

Liu, Na, Ning Jiang, Rui Guo, et al.. (2013). MiR-451 inhibits cell growth and invasion by targeting MIF and is associated with survival in nasopharyngeal carcinoma. Molecular Cancer. 12(1). 123–123. 103 indexed citations

20.

Pireddu, Roberta, Ying Sun, Nan Sun, et al.. (2012). RKI-1447 Is a Potent Inhibitor of the Rho-Associated ROCK Kinases with Anti-Invasive and Antitumor Activities in Breast Cancer. Cancer Research. 72(19). 5025–5034. 123 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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