Eun Suk

1.1k citations
46 papers · 816 · h-index 14

Impact in

Papers in

Eun Suk

43 papers receiving 785 citations

Peers

Eun Suk
Comparison fields: 5 of 62
  • Radiology, Nuclear Medicine and Imaging 502
  • Pathology and Forensic Medicine 293
  • Cancer Research 194
  • Dermatology 94
  • Oncology 165
Replace Caroline Malhaire with:
Caroline Malhaire France
Hiroko Tsunoda Japan
Ana P. Benveniste United States
MJ Michell United Kingdom
Volker Duda Germany
Elvira Ferreira Marques Brazil
Pat W. Whitworth United States
Carol B. Stelling United States
Antuono Latronico Italy
Yu‐Mee Sohn South Korea
Eun Suk relative to Caroline Malhaire France Caroline Malhaire's profile →
Citations per field
00.5×4.9×
Caroline Malhaire · 1×
Citations per year

Countries citing papers authored by Eun Suk

Since Specialization
Citations

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

Fields of papers citing papers by Eun Suk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009150
2 2007146
3 2003103
4 201377
5 201746
6 201433
7 200529
8 200729
9 201123
10 201419
11 201215
12 201415
13 200914
14 201013
15 201312
16 201110
17 20088
18 20138
19 20117
20 20107

About Eun Suk

Eun Suk is a scholar working on Pathology and Forensic Medicine, Radiology, Nuclear Medicine and Imaging, Cancer Research, Dermatology and Oncology, having authored 46 papers that have together received 816 indexed citations. Recurring topics across this work include Breast Lesions and Carcinomas (22 papers), Breast Cancer Treatment Studies (14 papers), Cancer and Skin Lesions (11 papers), MRI in cancer diagnosis (10 papers), Medical Imaging Techniques and Applications (8 papers), Digital Radiography and Breast Imaging (7 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and AI in cancer detection (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (502 citations), Pathology and Forensic Medicine (293 citations), Cancer Research (194 citations), Dermatology (94 citations) and Oncology (165 citations). Eun Suk has collaborated with scholars based in South Korea, United States and Germany. Frequent co-authors include Bong Joo Kang, Hyeon Sook Kim, Sung Hun Kim, Mi Jung Park, Yon Kwon Ihn, Jae Jeong Choi, Hak Hee Kim, Ji Han Jung, Young Jin Suh and Yong Gyu Park. Their work appears in journals such as Korean Journal of Radiology, Archives of Gynecology and Obstetrics, ULTRASONOGRAPHY, Journal of Ultrasound in Medicine and Breast Cancer.

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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