Kwang Gi Kim

8.5k citations
387 papers · 6.0k indexed · h-index 41
Topics
Radiomics and Machine Learning in Medical Imaging (45 papers)Glaucoma and retinal disorders (36 papers)AI in cancer detection (24 papers)
Journals
Nature CommunicationsThe Journal of Experimental MedicineSHILAP Revista de lepidopterología

In The Last Decade

Kwang Gi Kim

351 papers receiving 5.8k citations

Peers

Kwang Gi Kim
Comparison fields: 5 of 182
  • Radiology, Nuclear Medicine and Imaging 2.5k
  • Pulmonary and Respiratory Medicine 1.3k
  • Biomedical Engineering 1.2k
  • Oncology 924
  • Surgery 570
Replace Takeshi Hara with:
Takeshi Hara Japan
Luca Brunese Italy
Alfonso Reginelli Italy
Salvatore Cappabianca Italy
Ming Li China
Amit Gupta United States
David Snead United Kingdom
Yukio Miki Japan
Namkug Kim South Korea
Min Jung Kim South Korea
Kwang Gi Kim relative to Takeshi Hara Japan Takeshi Hara's profile →
Citations per field
00.5×3.2×
Takeshi Hara · 1×
Citations per year

Countries citing papers authored by Kwang Gi Kim

Since Specialization
Citations

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

Fields of papers citing papers by Kwang Gi Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kwang Gi Kim. 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 Kwang Gi Kim. The network helps show where Kwang Gi Kim may publish in the future.

Co-authorship network of co-authors of Kwang Gi Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Kwang Gi Kim. A scholar is included among the top collaborators of Kwang Gi Kim 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 Kwang Gi Kim. Kwang Gi Kim 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 2
3 6
4 3
5 1
6 0
7 5
8 5
9 1
10 10
11 1
12 2
13 8
14 26
15 1
16 2
17 4
18 143
19 252
20 26

About Kwang Gi Kim

Kwang Gi Kim is a scholar working on Health Informatics, Ophthalmology and Radiology, Nuclear Medicine and Imaging, having authored 387 papers that have together received 6.0k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (45 papers), Glaucoma and retinal disorders (36 papers) and AI in cancer detection (24 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (2.5k citations), Health Informatics (132 citations) and Ophthalmology (566 citations). Kwang Gi Kim has collaborated with scholars based in South Korea, United States and Ethiopia. Frequent co-authors include Young Jae Kim, Jin Mo Goo, Chang Min Park, Pin Wang, Hyun Ju Lee, Chang Hyun Lee, Natnaree Siriwon, Seung Hong Choi, Kyongtae T. Bae and Jeong‐Min Hwang. Their work appears in journals such as Nature Communications, The Journal of Experimental Medicine and SHILAP Revista de lepidopterología.

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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