Ju Gang Nam

1.9k citations
43 papers · 1.3k indexed · 1 hit paper · h-index 19
Topics
Lung Cancer Diagnosis and Treatment (17 papers)Radiomics and Machine Learning in Medical Imaging (14 papers)COVID-19 diagnosis using AI (11 papers)

In The Last Decade

Ju Gang Nam

41 papers receiving 1.3k citations

Hit Papers

Development and Validation of Deep Learning–based Automat...20182026202020232018100200300

Peers

Ju Gang Nam
Comparison fields: 5 of 102
  • Radiology, Nuclear Medicine and Imaging 988
  • Pulmonary and Respiratory Medicine 517
  • Biomedical Engineering 241
  • Health Informatics 210
  • Artificial Intelligence 171
Replace Masahiro Yanagawa with:
Masahiro Yanagawa Japan
John Mongan United States
Satheesh Krishna Canada
Xueqian Xie China
Orit Shimon Israel
Christoph Wald United States
Ramandeep Singh United States
Ian Pan United States
Simon Lennartz Germany
Roberto Lo Gullo United States
Ju Gang Nam relative to Masahiro Yanagawa Japan Masahiro Yanagawa's profile →
Citations per field
00.5×1.5×
Masahiro Yanagawa · 1×
Citations per year

Countries citing papers authored by Ju Gang Nam

Since Specialization
Citations

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

Fields of papers citing papers by Ju Gang Nam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ju Gang Nam. 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 Ju Gang Nam. The network helps show where Ju Gang Nam may publish in the future.

Co-authorship network of co-authors of Ju Gang Nam

This figure shows the co-authorship network connecting the top 25 collaborators of Ju Gang Nam. A scholar is included among the top collaborators of Ju Gang Nam 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 Ju Gang Nam. Ju Gang Nam 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
#WorkIndexed citations
1 0
2 69
3 15
4 5
5 9
6 9
7 23
8 9
9 5
10 46
11 31
12 20
13 27
14 29
15 44
16 34
17 73
18 121
19 9
20 21

About Ju Gang Nam

Ju Gang Nam is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics and Pulmonary and Respiratory Medicine, having authored 43 papers that have together received 1.3k indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (17 papers), Radiomics and Machine Learning in Medical Imaging (14 papers) and COVID-19 diagnosis using AI (11 papers). The work is most often cited by research in Health Informatics (210 citations), Radiology, Nuclear Medicine and Imaging (988 citations) and Pulmonary and Respiratory Medicine (517 citations). Ju Gang Nam has collaborated with scholars based in South Korea, Ethiopia and United States. Frequent co-authors include Jin Mo Goo, Chang Min Park, Eui Jin Hwang, Jong Hyuk Lee, Sunggyun Park, Sangheum Hwang, Kun Young Lim, Jae Ho Sohn, Kwang-Nam Jin and Jung Hee Hong. Their work appears in journals such as PLoS ONE, American Journal of Respiratory and Critical Care Medicine and Radiology.

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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