Chan‐Won Kim

44 papers receiving 1.5k citations

Peers

Chan‐Won Kim
Comparison fields: 5 of 122
  • Endocrinology, Diabetes and Metabolism 446
  • Hepatology 147
  • Experimental and Cognitive Psychology 237
  • Epidemiology 584
  • Physiology 393
Replace Tanefa A. Apekey with:
Tanefa A. Apekey United Kingdom
Phyliss Sholinsky United States
Pierre‐Yves Benhamou France
Olivier Phan France
Rasa Kazlauskaite United States
Ginger Smith Carls United States
Ju Young Jung South Korea
Qingshan Geng China
John A. Linton South Korea
Tamara S. Hannon United States
Chan‐Won Kim relative to Tanefa A. Apekey United Kingdom Tanefa A. Apekey's profile →
Citations per field
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Tanefa A. Apekey · 1×
Citations per year

Countries citing papers authored by Chan‐Won Kim

Since Specialization
Citations

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

Fields of papers citing papers by Chan‐Won Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chan‐Won 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 Chan‐Won Kim. The network helps show where Chan‐Won Kim may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016162
2 2015157
3 2013151
4 201687
5 201178
6 201274
7 201571
8 201252
9 201451
10 201547
11 201547
12 201342
13 201337
14 201437
15 201835
16 201830
17 201229
18 201727
19 200323
20 201021

About Chan‐Won Kim

Chan‐Won Kim is a scholar working on Epidemiology, Cardiology and Cardiovascular Medicine, Endocrinology, Diabetes and Metabolism, Physiology and Public Health, Environmental and Occupational Health, having authored 50 papers that have together received 1.5k indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (14 papers), Sleep and related disorders (7 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (7 papers), Cardiovascular Function and Risk Factors (7 papers), Diet, Metabolism, and Disease (6 papers), Sleep and Work-Related Fatigue (5 papers), Obesity, Physical Activity, Diet (4 papers) and Nutrition and Health in Aging (4 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (446 citations), Hepatology (147 citations), Experimental and Cognitive Psychology (237 citations), Epidemiology (584 citations) and Physiology (393 citations). Chan‐Won Kim has collaborated with scholars based in South Korea, United States and Malaysia. Frequent co-authors include Yoosoo Chang, Seungho Ryu, Hyun Suk Jung, Kyung Eun Yun, Ho Cheol Shin, Min‐Jung Kwon, Juhee Cho, Eunju Sung, Eun Chul Chung and Yuni Choi. Their work appears in journals such as Journal of Hepatology, Arteriosclerosis Thrombosis and Vascular Biology, Circulation Journal, PLoS ONE and Journal of Korean Medical Science.

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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