Dae-Sik Ko

44 papers receiving 351 citations

Peers

Dae-Sik Ko
Comparison fields: 5 of 106
  • Biophysics 86
  • Physical Therapy, Sports Therapy and Rehabilitation 28
  • Rehabilitation 30
  • Leadership and Management 6
  • Medical Laboratory Technology 4
Replace Junkai Xu with:
Junkai Xu China
Shekhar Hansda India
Bin Yin China
Zi Ye China
Xianliang Chen China
Sandra Morelli Italy
Nicolás Paris France
David T. Marc United States
Kenneth L. Watkin United States
Kimberley A. Frederick United States
Dae-Sik Ko relative to Junkai Xu China Junkai Xu's profile →
Citations per field
00.5×10×20×28.7×
Junkai Xu · 1×
Citations per year

Countries citing papers authored by Dae-Sik Ko

Since Specialization
Citations

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

Fields of papers citing papers by Dae-Sik Ko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dae-Sik Ko. 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 Dae-Sik Ko. The network helps show where Dae-Sik Ko may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199681
2 201347
3 199645
4 201036
5 201226
6 201523
7 201420
8 199715
9 20149
10 20098
11 20137
12 20196
13 19925
14 20145
15 20135
16 20125
17 20035
18 20184
19 20174
20 20134

About Dae-Sik Ko

Dae-Sik Ko is a scholar working on Computer Networks and Communications, Pharmacology, General Health Professions, Information Systems and Biomedical Engineering, having authored 61 papers that have together received 405 indexed citations. Recurring topics across this work include Musculoskeletal pain and rehabilitation (9 papers), Health and Wellbeing Research (8 papers), Balance, Gait, and Falls Prevention (6 papers), Internet of Things and Social Network Interactions (6 papers), Stroke Rehabilitation and Recovery (5 papers), Nutrition, Health and Food Behavior (4 papers), Diverse Approaches in Healthcare and Education Studies (4 papers) and Innovation in Digital Healthcare Systems (4 papers). The work is most often cited by research in Biophysics (86 citations), Physical Therapy, Sports Therapy and Rehabilitation (28 citations), Rehabilitation (30 citations), Leadership and Management (6 citations) and Medical Laboratory Technology (4 citations). Dae-Sik Ko has collaborated with scholars based in South Korea, Germany and United States. Frequent co-authors include Markus Sauer, Dae-In Jung, Ji‐Hyuk Park, K. H. Drexhage, C. Zander, J. Wolfrum, Leif Brand, Mi‐Ae Jeong, Christian Eggeling and Claus A. M. Seidel. Their work appears in journals such as Chemical Physics Letters, IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control, Applied Sciences, Optics Communications and Personal and Ubiquitous Computing.

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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