Jaehyuk Cho
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Safety, Risk, Reliability and Quality top 5%
- Computer Vision and Pattern Recognition top 10%
- Biomedical Engineering
- Co-authors
- V E SathishkumarMalliga SubramanianSungeun KimJae Gol ChoeJae Seon EoYoungsuk SeoH. Thameem BashaKisoo Pahk
- Topics
- Radiomics and Machine Learning in Medical Imaging (7 papers)Artificial Intelligence in Healthcare (6 papers)Air Quality Monitoring and Forecasting (6 papers)
- Cited by
- Safety, Risk, Reliability and QualityRadiology, Nuclear Medicine and ImagingComputer Vision and Pattern Recognition
- Partner nations
- South KoreaIndiaMalaysia
In The Last Decade
Jaehyuk Cho
56 papers receiving 625 citations
Hit Papers
Peers
Comparison fields: 5 of 122
- Artificial Intelligence 125
- Radiology, Nuclear Medicine and Imaging 117
- Safety, Risk, Reliability and Quality 114
- Computer Vision and Pattern Recognition 98
- Biomedical Engineering 72
Countries citing papers authored by Jaehyuk Cho
This map shows the geographic impact of Jaehyuk Cho'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 Jaehyuk Cho with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jaehyuk Cho more than expected).
Fields of papers citing papers by Jaehyuk Cho
This network shows the impact of papers produced by Jaehyuk Cho. 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 Jaehyuk Cho. The network helps show where Jaehyuk Cho may publish in the future.
Co-authorship network of co-authors of Jaehyuk Cho
This figure shows the co-authorship network connecting the top 25 collaborators of Jaehyuk Cho. A scholar is included among the top collaborators of Jaehyuk Cho 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 Jaehyuk Cho. Jaehyuk Cho is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 1 | |
| 3 | 4 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 11 | |
| 9 | 2 | |
| 10 | 8 | |
| 11 | 0 | |
| 12 | 7 | |
| 13 | 8 | |
| 14 | 4 | |
| 15 | 1 | |
| 16 | 11 | |
| 17 | 12 | |
| 18 | 0 | |
| 19 | 12 | |
| 20 | 19 |
About Jaehyuk Cho
Jaehyuk Cho is a scholar working on Health Information Management, Leadership and Management and Issues, ethics and legal aspects, having authored 69 papers that have together received 648 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (7 papers), Artificial Intelligence in Healthcare (6 papers) and Air Quality Monitoring and Forecasting (6 papers). The work is most often cited by research in Safety, Risk, Reliability and Quality (114 citations), Radiology, Nuclear Medicine and Imaging (117 citations) and Computer Vision and Pattern Recognition (98 citations). Jaehyuk Cho has collaborated with scholars based in South Korea, India and Malaysia. Frequent co-authors include V E Sathishkumar, Malliga Subramanian, Sungeun Kim, Jae Gol Choe, Jae Seon Eo, Youngsuk Seo, H. Thameem Basha, Kisoo Pahk, Kogilavani Shanmugavadivel and Shaik Jakeer. Their work appears in journals such as PLoS ONE, Scientific Reports and IEEE Access.
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.