Hyoeun Kim
- Molecular Biology
- Cancer Research top 10%
- Computer Vision and Pattern Recognition top 5%
- Cardiology and Cardiovascular Medicine top 10%
- Surgery
- Co-authors
- Hyeonseob NamHyunjae LeeBoyoung JoungDasom MunNuri YunSangheum HwangJi-Hoon JeongHee Jin Kim
- Topics
- Extracellular vesicles in disease (10 papers)Cardiomyopathy and Myosin Studies (8 papers)Nutrition and Health in Aging (5 papers)
- Partner nations
- South KoreaUnited StatesUnited Kingdom
In The Last Decade
Hyoeun Kim
82 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 163
- Molecular Biology 597
- Cancer Research 298
- Computer Vision and Pattern Recognition 218
- Cardiology and Cardiovascular Medicine 210
- Surgery 200
Countries citing papers authored by Hyoeun Kim
This map shows the geographic impact of Hyoeun 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 Hyoeun Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hyoeun Kim more than expected).
Fields of papers citing papers by Hyoeun Kim
This network shows the impact of papers produced by Hyoeun 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 Hyoeun Kim. The network helps show where Hyoeun Kim may publish in the future.
Co-authorship network of co-authors of Hyoeun Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Hyoeun Kim. A scholar is included among the top collaborators of Hyoeun Kim based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hyoeun Kim. Hyoeun Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 11 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 39 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 3 | |
| 12 | 192 | |
| 13 | 6 | |
| 14 | 1 | |
| 15 | Batch-Instance Normalization for Adaptively Style-Invariant Neural Networks | 34 |
| 16 | 0 | |
| 17 | Scale-Invariant Feature Learning using Deconvolutional Neural Networks for Weakly-Supervised Semantic Segmentation. | 11 |
| 18 | The education program majored in fashion for improving interest in schoolwork | 1 |
| 19 | Changes in Student Nurses' Perception between Initial and Final Clinical Practice | 2 |
| 20 | A Study on The Manufacturing Industries of Women's Wear in Taegu Through the Sewing Technicians | 1 |
About Hyoeun Kim
Hyoeun Kim is a scholar working on Cardiology and Cardiovascular Medicine, Leadership and Management and Geriatrics and Gerontology, having authored 98 papers that have together received 1.7k indexed citations. Recurring topics across this work include Extracellular vesicles in disease (10 papers), Cardiomyopathy and Myosin Studies (8 papers) and Nutrition and Health in Aging (5 papers). The work is most often cited by research in Cancer Research (298 citations), Rheumatology (189 citations) and Computer Vision and Pattern Recognition (218 citations). Hyoeun Kim has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Hyeonseob Nam, Hyunjae Lee, Boyoung Joung, Dasom Mun, Nuri Yun, Sangheum Hwang, Ji-Hoon Jeong, Hee Jin Kim, Hyelim Park and Hyewon Park. Their work appears in journals such as Nature, Nature Communications and Journal of the American College of Cardiology.
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.