Young Dae Kim

11.5k citations
428 papers · 7.0k indexed · 1 hit paper · h-index 42

Impact in

Papers in

Young Dae Kim

411 papers receiving 6.9k citations

Hit Papers

Machine Learning–Based Model for Prediction of Outcomes in Acute Stroke 2019 · 405 citations
4052019202620212023100200300400

Peers

Young Dae Kim
Comparison fields: 5 of 184
  • Internal Medicine 709
  • Epidemiology 2.9k
  • Rehabilitation 544
  • Neurology 1.1k
  • Cardiology and Cardiovascular Medicine 1.4k
Replace Ji Sung Lee with:
Ji Sung Lee South Korea
Keiichi Fukuda Japan
Thomas Leung Hong Kong
James Sayre United States
Hölger Thiele Germany
Michael H. Lev United States
Kunihiro Nishimura Japan
Junbo Ge China
Urs Fischer Switzerland
Joachim E. Wildberger Netherlands
Young Dae Kim relative to Ji Sung Lee South Korea Ji Sung Lee's profile →
Citations per field
00.5×1.5×1.8×
Ji Sung Lee · 1×
Citations per year

Countries citing papers authored by Young Dae Kim

Since Specialization
Citations

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

Fields of papers citing papers by Young Dae Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20245
2 20240
3 20240
4 20230
5 20230
6 20235
7 20237
8 20221
9 20221
10 202116
11 202010
12 201925
13 201961
14 2018109
15 201894
16 20164
17 201336
18 20121
19 20122
20
Education and Training Guidelines for the Board of the Korean Society of Gastrointestinal Endoscopy
20118

About Young Dae Kim

Young Dae Kim is a scholar working on Internal Medicine, Cardiology and Cardiovascular Medicine, Epidemiology, Neurology and Pulmonary and Respiratory Medicine, having authored 428 papers that have together received 7.0k indexed citations. Recurring topics across this work include Acute Ischemic Stroke Management (157 papers), Cerebrovascular and Carotid Artery Diseases (87 papers), Venous Thromboembolism Diagnosis and Management (58 papers), Atrial Fibrillation Management and Outcomes (45 papers), Cardiac Imaging and Diagnostics (29 papers), Stroke Rehabilitation and Recovery (23 papers), Vibration Control and Rheological Fluids (22 papers) and Seismic Performance and Analysis (20 papers). The work is most often cited by research in Internal Medicine (709 citations), Epidemiology (2.9k citations), Rehabilitation (544 citations), Neurology (1.1k citations) and Cardiology and Cardiovascular Medicine (1.4k citations). Young Dae Kim has collaborated with scholars based in South Korea, United States and Canada. Frequent co-authors include Ji Hoe Heo, Hyo Suk Nam, Hye Sun Lee, Jinkwon Kim, Chung Mo Nam, Tae-Jin Song, Hyungjong Park, Dong Joon Kim, Dongbeom Song and Byung Moon Kim. Their work appears in journals such as Stroke, Journal of Stroke, PLoS ONE, Frontiers in Neurology and European Journal of Neurology.

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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