Kyu-Hwan Jung
- Radiology, Nuclear Medicine and Imaging top 2%
- Artificial Intelligence top 5%
- Ophthalmology top 2%
- Computer Vision and Pattern Recognition top 5%
- Pulmonary and Respiratory Medicine top 10%
- Co-authors
- Jaemin SonSang Jun ParkJae‐Young KimIn‐Seok SongJoon Beom SeoKyu Hyung ParkJoo Young ShinJaewook Lee
- Topics
- Radiomics and Machine Learning in Medical Imaging (8 papers)Lung Cancer Diagnosis and Treatment (7 papers)COVID-19 diagnosis using AI (7 papers)
- Journals
- Journal of Clinical OncologySHILAP Revista de lepidopterologíaNeurology
- Partner nations
- South KoreaUnited StatesGermany
In The Last Decade
Kyu-Hwan Jung
37 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 97
- Radiology, Nuclear Medicine and Imaging 679
- Artificial Intelligence 264
- Ophthalmology 232
- Computer Vision and Pattern Recognition 226
- Pulmonary and Respiratory Medicine 215
Countries citing papers authored by Kyu-Hwan Jung
This map shows the geographic impact of Kyu-Hwan Jung'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 Kyu-Hwan Jung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyu-Hwan Jung more than expected).
Fields of papers citing papers by Kyu-Hwan Jung
This network shows the impact of papers produced by Kyu-Hwan Jung. 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 Kyu-Hwan Jung. The network helps show where Kyu-Hwan Jung may publish in the future.
Co-authorship network of co-authors of Kyu-Hwan Jung
This figure shows the co-authorship network connecting the top 25 collaborators of Kyu-Hwan Jung. A scholar is included among the top collaborators of Kyu-Hwan Jung 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 Kyu-Hwan Jung. Kyu-Hwan Jung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 17 | |
| 6 | 6 | |
| 7 | 2 | |
| 8 | 17 | |
| 9 | 18 | |
| 10 | 17 | |
| 11 | 31 | |
| 12 | 57 | |
| 13 | 56 | |
| 14 | 145 | |
| 15 | 169 | |
| 16 | 16 | |
| 17 | 146 | |
| 18 | Semi-Supervised Reinforced Active Learning for Pulmonary Nodule Detection in Chest X-rays | 1 |
| 19 | 81 | |
| 20 | 27 |
About Kyu-Hwan Jung
Kyu-Hwan Jung is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics and Ophthalmology, having authored 38 papers that have together received 1.1k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (8 papers), Lung Cancer Diagnosis and Treatment (7 papers) and COVID-19 diagnosis using AI (7 papers). The work is most often cited by research in Health Informatics (78 citations), Radiology, Nuclear Medicine and Imaging (679 citations) and Ophthalmology (232 citations). Kyu-Hwan Jung has collaborated with scholars based in South Korea, United States and Germany. Frequent co-authors include Jaemin Son, Sang Jun Park, Jae‐Young Kim, In‐Seok Song, Joon Beom Seo, Kyu Hyung Park, Joo Young Shin, Jaewook Lee, Sang Min Lee and Sohee Park. Their work appears in journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and 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.