Chunli Kong

1.9k total citations
54 papers, 1.4k citations indexed

About

Chunli Kong is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Chunli Kong has authored 54 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 14 papers in Pulmonary and Respiratory Medicine and 14 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Chunli Kong's work include Radiomics and Machine Learning in Medical Imaging (14 papers), Infant Nutrition and Health (10 papers) and Digestive system and related health (9 papers). Chunli Kong is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (14 papers), Infant Nutrition and Health (10 papers) and Digestive system and related health (9 papers). Chunli Kong collaborates with scholars based in China, Netherlands and Germany. Chunli Kong's co-authors include Paul de Vos, Lianghui Cheng, Yongkang Luo, Jiansong Ji, Marthe T. C. Walvoort, Renate Akkerman, Qiaoyou Weng, Marijke M. Faas, Chenying Lu and Dapeng Li and has published in prestigious journals such as Food Chemistry, Journal of Nutrition and Carbohydrate Polymers.

In The Last Decade

Chunli Kong

48 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chunli Kong China 21 542 381 378 231 229 54 1.4k
Changfeng Li China 25 1.1k 2.1× 417 1.1× 701 1.9× 733 3.2× 26 0.1× 67 2.4k
Hongxin Zhang China 22 426 0.8× 86 0.2× 78 0.2× 242 1.0× 33 0.1× 56 1.5k
Gian G. Re United States 19 1.2k 2.1× 144 0.4× 257 0.7× 117 0.5× 35 0.2× 35 1.7k
Liping Yang China 27 995 1.8× 47 0.1× 145 0.4× 363 1.6× 162 0.7× 114 1.9k
Keiko Ishikawa Japan 24 765 1.4× 80 0.2× 144 0.4× 84 0.4× 16 0.1× 91 1.9k
Ming Tian China 16 663 1.2× 226 0.6× 103 0.3× 263 1.1× 105 0.5× 45 1.5k
Jun Feng China 21 692 1.3× 62 0.2× 125 0.3× 86 0.4× 18 0.1× 141 1.6k
Stefan Schülke Germany 21 440 0.8× 105 0.3× 65 0.2× 82 0.4× 17 0.1× 52 1.8k
Nobuhiro Ueno Japan 23 729 1.3× 159 0.4× 492 1.3× 98 0.4× 17 0.1× 104 1.8k
Doerthe Kuester Germany 28 649 1.2× 86 0.2× 447 1.2× 254 1.1× 15 0.1× 83 2.3k

Countries citing papers authored by Chunli Kong

Since Specialization
Citations

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

Fields of papers citing papers by Chunli Kong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chunli Kong

This figure shows the co-authorship network connecting the top 25 collaborators of Chunli Kong. A scholar is included among the top collaborators of Chunli Kong 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 Chunli Kong. Chunli Kong 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.
Akram, Muhammad, Rashid Iqbal, Abdullah Alghamdi, et al.. (2025). EFFECT OF DIFFERENT FERTILIZATION COMBINATIONS ON CHINESE CABBAGE QUALITY, AMINO ACID CONTENT, AND RHIZOSPHERE MICROORGANISMS. Applied Ecology and Environmental Research. 23(3). 5699–5720.
2.
Zhang, Yu, et al.. (2025). PLASTIC FILM ALTERS SOIL PHYSICOCHEMICAL PROPERTIES AND MICROORGANISMS, AFFECTING THE GROWTH OF CIGAR TOBACCO. Applied Ecology and Environmental Research. 23(2). 3541–3554.
4.
He, Xiaoyu, Yujie Chen, Chunli Kong, et al.. (2025). Correlation analysis of monosaccharide composition and in vitro antioxidant and hypoglycemic activities of Tremella fuciformis spore polysaccharides. Food Chemistry. 498(Pt 1). 147066–147066.
5.
Chen, Weiyue, Xia Li, Weibo Mao, et al.. (2024). Dual-energy computed tomography for predicting histological grading and survival in patients with pancreatic ductal adenocarcinoma. European Radiology. 35(5). 2818–2832. 2 indexed citations
6.
7.
Liu, Xinghao, Yajun Cui, Siyi Chen, et al.. (2024). Molecular investigation of soybean protein for improving the stability of quinoa (Chenopodium quinoa willd.) milk substitute. Food Chemistry. 461. 140829–140829. 2 indexed citations
8.
Tu, Jianfei, Weiyue Chen, Chunli Kong, et al.. (2024). Dual-energy computed tomography for predicting cervical lymph node metastasis in laryngeal squamous cell carcinoma. Heliyon. 10(16). e35528–e35528. 1 indexed citations
9.
Kong, Chunli, Liyun Zheng, Shiji Fang, et al.. (2023). Predictive Models for Colon Adenocarcinoma Diagnosis, Prognosis, and Immune Microenvironment Based on 2 Hypoxia-Related Genes: KDM3A and ENO3. Technology in Cancer Research & Treatment. 22. 2223937382–2223937382. 1 indexed citations
12.
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
13.
Chen, Mingzhen, Chunli Kong, Enqi Qiao, et al.. (2023). Multi-algorithms analysis for pre-treatment prediction of response to transarterial chemoembolization in hepatocellular carcinoma on multiphase MRI. Insights into Imaging. 14(1). 38–38. 14 indexed citations
15.
Beukema, Martin, Madelon J. Logtenberg, Renate Akkerman, et al.. (2022). The level and distribution of methyl-esters influence the impact of pectin on intestinal T cells, microbiota, and Ahr activation. Carbohydrate Polymers. 286. 119280–119280. 20 indexed citations
16.
Kong, Chunli, Zhongwei Zhao, Weiyue Chen, et al.. (2021). Prediction of tumor response via a pretreatment MRI radiomics-based nomogram in HCC treated with TACE. European Radiology. 31(10). 7500–7511. 97 indexed citations
17.
Beukema, Martin, Renate Akkerman, Chunli Kong, et al.. (2021). Pectins that Structurally Differ in the Distribution of Methyl‐Esters Attenuate Citrobacter rodentium‐Induced Colitis. Molecular Nutrition & Food Research. 65(19). e2100346–e2100346. 21 indexed citations
18.
Kong, Chunli, Martin Beukema, Min Wang, Bart J. de Haan, & Paul de Vos. (2021). Human milk oligosaccharides and non-digestible carbohydrates prevent adhesion of specific pathogensviamodulating glycosylation or inflammatory genes in intestinal epithelial cells. Food & Function. 12(17). 8100–8119. 16 indexed citations
19.
Tang, Bufu, Jinyu Zhu, Jie Li, et al.. (2020). The ferroptosis and iron-metabolism signature robustly predicts clinical diagnosis, prognosis and immune microenvironment for hepatocellular carcinoma. Cell Communication and Signaling. 18(1). 174–174. 170 indexed citations
20.
Kong, Chunli, Huiyi Wang, Dapeng Li, et al.. (2016). Quality changes and predictive models of radial basis function neural networks for brined common carp (Cyprinus carpio) fillets during frozen storage. Food Chemistry. 201. 327–333. 53 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026