Jae Won Yang

2.5k citations
77 papers · 1.3k · h-index 18

Impact in

  • Nephrology top 5%
    • Dialysis and Renal Disease Management
    • Renal Diseases and Glomerulopathies
    • COVID-19 Clinical Research Studies
    • SARS-CoV-2 and COVID-19 Research

Papers in

    • Dialysis and Renal Disease Management 6
    • Renal Diseases and Glomerulopathies 6
    • Chronic Kidney Disease and Diabetes 4

Jae Won Yang

72 papers receiving 1.3k citations

Peers

Jae Won Yang
Comparison fields: 5 of 107
  • Nephrology 148
  • Infectious Diseases 237
  • Neurology 111
  • Biological Psychiatry 14
  • Physiology 143
Replace Qiongjing Yuan with:
Qiongjing Yuan China
Antoni Castro Spain
Yan Qin China
Vijay Gayam United States
Sridhar Chilimuri United States
Dhrubajyoti Bandyopadhyay United States
Cheng Wan China
Chan‐Duck Kim South Korea
Michele F. Eisenga Netherlands
Jae Won Yang relative to Qiongjing Yuan China Qiongjing Yuan's profile →
Citations per field
00.5×3.5×
Qiongjing Yuan · 1×
Citations per year

Countries citing papers authored by Jae Won Yang

Since Specialization
Citations

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

Fields of papers citing papers by Jae Won Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jae Won Yang. 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 Jae Won Yang. The network helps show where Jae Won Yang may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 77 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020329
2 202092
3 202078
4 202051
5 201349
6 202245
7 201840
8 202240
9 201940
10 201931
11 201831
12 201327
13 201727
14 202025
15 201922
16 202222
17 201822
18 201718
19 202015
20 202015

About Jae Won Yang

Jae Won Yang is a scholar working on Nephrology, Molecular Biology, Physiology, Infectious Diseases and Surgery, having authored 77 papers that have together received 1.3k indexed citations. Recurring topics across this work include Dialysis and Renal Disease Management (6 papers), Body Composition Measurement Techniques (6 papers), Renal Diseases and Glomerulopathies (6 papers), Chronic Kidney Disease and Diabetes (4 papers), Hepatitis C virus research (4 papers), COVID-19 Clinical Research Studies (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers) and Long-Term Effects of COVID-19 (3 papers). The work is most often cited by research in Nephrology (148 citations), Infectious Diseases (237 citations), Neurology (111 citations), Biological Psychiatry (14 citations) and Physiology (143 citations). Jae Won Yang has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Jun Young Lee, Jae Il Shin, Andreas Kronbichler, Keum Hwa Lee, Jae‐Seok Kim, Byoung Geun Han, Jae Seok Kim, Maria Effenberger, Wladimir Szpirt and Seung Ok Choi. Their work appears in journals such as Kidney Research and Clinical Practice, Nutrients, PLoS ONE, Journal of Clinical Medicine and Microscopy and Microanalysis.

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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