Junyun Li

40 papers receiving 861 citations

Junyun Li's Hit Papers

Deep Learning for Automated Contouring of Primary Tumor Volumes by MRI for Nasopharyngeal Carcinoma 2019 · 250 citations
2500+2+4Years since publication50100150200250

Peers

Junyun Li
Comparison fields: 5 of 99
  • Otorhinolaryngology 87
  • Health Informatics 23
  • Earth-Surface Processes 86
  • Atmospheric Science 183
  • Radiation 66
Replace Silvia Capuani with:
Silvia Capuani Italy
Dennis R. Schaart Netherlands
A. Arnold Germany
Yutaka Shiraishi Japan
David Haberthür Switzerland
T. E. Smith Canada
Vincent Meyer France
Lauren E. Howard United States
Daniele Panetta Italy
Thomas Frisch France
Junyun Li relative to Silvia Capuani Italy Silvia Capuani's profile →
Citations per field
00.5×10×20×30×43.5×
Silvia Capuani · 1×
Citations per year

Countries citing papers authored by Junyun Li

Since Specialization
Citations

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

Fields of papers citing papers by Junyun Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Junyun Li, 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 Junyun Li Line = papers co-authored together Junyun Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep Learning for Automated Contouring of Primary Tumor Volumes by MRI for Nasopharyngeal Carcinoma
Hit paper breakdown →
2019250
2 200090
3 202088
4 202141
5 199537
6 201533
7 202133
8 201732
9 202329
10 202129
11 202123
12 202122
13 202021
14 201717
15 202116
16 201314
17 201712
18 201911
19 201910
20 19999

About Junyun Li

Junyun Li is a scholar working on Atmospheric Science, Anthropology, Atomic and Molecular Physics, and Optics, Obstetrics and Gynecology and Earth-Surface Processes, having authored 40 papers that have together received 878 indexed citations. Recurring topics across this work include Geology and Paleoclimatology Research (13 papers), Pleistocene-Era Hominins and Archaeology (8 papers), Atomic and Subatomic Physics Research (7 papers), Endometrial and Cervical Cancer Treatments (7 papers), Karst Systems and Hydrogeology (5 papers), Geological formations and processes (4 papers), Advanced Sensor and Energy Harvesting Materials (4 papers) and Isotope Analysis in Ecology (3 papers). The work is most often cited by research in Otorhinolaryngology (87 citations), Health Informatics (23 citations), Earth-Surface Processes (86 citations), Atmospheric Science (183 citations) and Radiation (66 citations). Junyun Li has collaborated with scholars based in China, Taiwan and Germany. Frequent co-authors include Zefei Peng, Ting‐Yong Li, Chuan‐Chou Shen, Lan Liu, Hai Cheng, Chuan-Miao Xie, Yueming Jin, Brian Cowan, Feng Liu and Qi Dou. Their work appears in journals such as Journal of Low Temperature Physics, Quaternary Science Reviews, Quaternary International, Palaeogeography Palaeoclimatology Palaeoecology and Scientific Reports.

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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