Ryoungwoo Jang
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Pulmonary and Respiratory Medicine
- Topics
- COVID-19 diagnosis using AI (6 papers)Radiomics and Machine Learning in Medical Imaging (3 papers)AI in cancer detection (3 papers)
- Partner nations
- South Korea
In The Last Decade
Ryoungwoo Jang
8 papers receiving 388 citations
Peers
Comparison fields: 5 of 91
- Radiology, Nuclear Medicine and Imaging 214
- Artificial Intelligence 124
- Biomedical Engineering 113
- Computer Vision and Pattern Recognition 51
- Pulmonary and Respiratory Medicine 49
Countries citing papers authored by Ryoungwoo Jang
This map shows the geographic impact of Ryoungwoo Jang'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 Ryoungwoo Jang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryoungwoo Jang more than expected).
Fields of papers citing papers by Ryoungwoo Jang
This network shows the impact of papers produced by Ryoungwoo Jang. 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 Ryoungwoo Jang. The network helps show where Ryoungwoo Jang may publish in the future.
Co-authorship network of co-authors of Ryoungwoo Jang
This figure shows the co-authorship network connecting the top 25 collaborators of Ryoungwoo Jang. A scholar is included among the top collaborators of Ryoungwoo Jang 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 Ryoungwoo Jang. Ryoungwoo Jang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 22 | |
| 2 | 6 | |
| 3 | 22 | |
| 4 | 59 | |
| 5 | 12 | |
| 6 | 34 | |
| 7 | 19 | |
| 8 | 224 |
About Ryoungwoo Jang
Ryoungwoo Jang is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 8 papers that have together received 398 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (6 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and AI in cancer detection (3 papers). The work is most often cited by research in Health Informatics (49 citations), Radiology, Nuclear Medicine and Imaging (214 citations) and Health Information Management (18 citations). Ryoungwoo Jang has collaborated with scholars based in South Korea. Frequent co-authors include Namkug Kim, Mingyu Kim, Keewon Shin, Jihye Yun, Hyun‐Jin Bae, Yongwon Cho, Jae Ho Choi, Jae Suk Chang, Pil Whan Yoon and Chul‐Ho Kim. Their work appears in journals such as Nature Communications, Scientific Reports and European Radiology.
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.