Zhoukun Ling

964 citations
6 papers · 567 · 1 hit paper · h-index 3

Impact in

Papers in

    • COVID-19 Clinical Research Studies 2
    • Diagnosis and treatment of tuberculosis 2
    • Infectious Diseases and Tuberculosis 1

Zhoukun Ling

4 papers receiving 552 citations

Zhoukun Ling's Hit Papers

Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2 2020 · 558 citations
5580+2+4Years since publication100200300400500

Peers

Zhoukun Ling
Comparison fields: 5 of 72
  • Infectious Diseases 321
  • Critical Care and Intensive Care Medicine 48
  • Neurology 116
  • Radiology, Nuclear Medicine and Imaging 133
  • General Dentistry 7
Replace Wanhua Guan with:
Wanhua Guan China
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Jinxin Liu China
Deyang Huang China
Songfeng Jiang China
Zhiping Zhang China
Xi Xu China
Kaihu Xiao China
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Zhoukun Ling relative to Wanhua Guan China Wanhua Guan's profile →
Citations per field
00.5×1.5×
Wanhua Guan · 1×
Citations per year

Countries citing papers authored by Zhoukun Ling

Since Specialization
Citations

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

Fields of papers citing papers by Zhoukun Ling

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Zhoukun Ling, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Zhoukun Ling Line = papers co-authored together Zhoukun Ling links everyone, so they are left out of the graph.

All Works

6 of 6 papers shown
#Work
1
Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2
Hit paper breakdown →
2020558
2 20204
3 20203
4 20202
5 20250
6 20250

About Zhoukun Ling

Zhoukun Ling is a scholar working on Infectious Diseases, Surgery, Radiology, Nuclear Medicine and Imaging, Hepatology and Organic Chemistry, having authored 6 papers that have together received 567 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (2 papers), COVID-19 Clinical Research Studies (2 papers), Diagnosis and treatment of tuberculosis (2 papers), Hepatocellular Carcinoma Treatment and Prognosis (2 papers), Infectious Diseases and Tuberculosis (1 paper) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Infectious Diseases (321 citations), Critical Care and Intensive Care Medicine (48 citations), Neurology (116 citations), Radiology, Nuclear Medicine and Imaging (133 citations) and General Dentistry (7 citations). Zhoukun Ling has collaborated with scholars based in China. Frequent co-authors include Wanhua Guan, Songfeng Jiang, Deyang Huang, Qingxin Gan, Bihua Chen, Chengcheng Yu, Jing Qu, Lieguang Zhang, Rui Jiang and Lin Lin. Their work appears in journals such as European Journal of Nuclear Medicine and Molecular Imaging, Liver International, Academic Radiology, Zhonghua fangshexian yixue zazhi and PubMed.

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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