Won Chul

1.2k citations
67 papers · 713 · h-index 16

Impact in

    • Artificial Intelligence in Healthcare and Education
    • Emergency and Acute Care Studies
    • Cardiac Arrest and Resuscitation
    • Trauma and Emergency Care Studies

Papers in

    • Cardiac Arrest and Resuscitation 9
    • Trauma and Emergency Care Studies 7
    • Emergency and Acute Care Studies 6
    • Sepsis Diagnosis and Treatment 4

Won Chul

65 papers receiving 697 citations

Peers

Won Chul
Comparison fields: 5 of 100
  • Health Informatics 62
  • Emergency Medicine 132
  • Health Information Management 65
  • Critical Care and Intensive Care Medicine 33
  • Emergency Medical Services 38
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Citations per field
00.5×2.8×
Brian W. Patterson · 1×
Citations per year

Countries citing papers authored by Won Chul

Since Specialization
Citations

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

Fields of papers citing papers by Won Chul

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202277
2 202039
3 201634
4 202032
5 201829
6 201828
7 202127
8 201823
9 201621
10 202319
11 202019
12 201517
13 201816
14 202116
15 202215
16 202215
17 202114
18 201914
19 202114
20 202014

About Won Chul

Won Chul is a scholar working on Emergency Medicine, Epidemiology, Health Information Management, Surgery and Emergency Medical Services, having authored 67 papers that have together received 713 indexed citations. Recurring topics across this work include Cardiac Arrest and Resuscitation (9 papers), Trauma and Emergency Care Studies (7 papers), Electronic Health Records Systems (6 papers), Emergency and Acute Care Studies (6 papers), Sepsis Diagnosis and Treatment (4 papers), Disaster Response and Management (3 papers), Hemodynamic Monitoring and Therapy (2 papers) and Machine Learning in Healthcare (2 papers). The work is most often cited by research in Health Informatics (62 citations), Emergency Medicine (132 citations), Health Information Management (65 citations), Critical Care and Intensive Care Medicine (33 citations) and Emergency Medical Services (38 citations). Won Chul has collaborated with scholars based in South Korea, United States and Singapore. Frequent co-authors include Junsang Yoo, Dong Kyung Chang, Sang Do Shin, Sung Yeon Hwang, Kyunga Kim, Tae Gun Shin, Taerim Kim, Hee Yoon, Minwoo Cho and Ho‐Young Lee. Their work appears in journals such as JMIR mhealth and uhealth, Journal of Korean Medical Science, Journal of Medical Internet Research, JMIR Serious Games and International Journal of Environmental Research and Public Health.

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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