Ji Eun Oh
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- Retinal Imaging and Analysis
Papers in
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- Radiomics and Machine Learning in Medical Imaging 9
- Medical Imaging Techniques and Applications 6
- Retinal Imaging and Analysis 3
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- Digital Radiography and Breast Imaging 9
- Lung Cancer Diagnosis and Treatment 2
- Co-authors
- Dae Kyung Sohn (5 shared papers)Joohyung Lee (5 shared papers)Kwang Gi Kim (5 shared papers)Hee Jin Chang (2 shared papers)Bo Yun Hur (4 shared papers)Min Ju Kim (3 shared papers)Jeong‐Min Hwang (3 shared papers)Hee Kyung Yang (3 shared papers)
- Journals
- Journal of Digital Imaging (2 papers)IEEE Access (2 papers)Optics and Lasers in Engineering (2 papers)Medicine (1 paper)BioMed Research International (1 paper)
- Partner nations
- South KoreaUnited StatesGermany
In The Last Decade
Ji Eun Oh
27 papers receiving 322 citations
Peers
Comparison fields: 5 of 65
- Radiology, Nuclear Medicine and Imaging 161
- Health Informatics 7
- Artificial Intelligence 97
- Genetics 26
- Leadership and Management 3
Countries citing papers authored by Ji Eun Oh
This map shows the geographic impact of Ji Eun Oh'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 Ji Eun Oh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ji Eun Oh more than expected).
Fields of papers citing papers by Ji Eun Oh
This network shows the impact of papers produced by Ji Eun Oh. 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 Ji Eun Oh. The network helps show where Ji Eun Oh may publish in the future.
Co-authors
The 25 scholars most cited alongside Ji Eun Oh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 60 | |
| 2 | 2018 | 47 | |
| 3 | 2010 | 43 | |
| 4 | 2016 | 35 | |
| 5 | 2019 | 28 | |
| 6 | 2015 | 19 | |
| 7 | 2018 | 17 | |
| 8 | 2018 | 13 | |
| 9 | 2019 | 13 | |
| 10 | 2018 | 8 | |
| 11 | 2024 | 7 | |
| 12 | 2018 | 6 | |
| 13 | 2018 | 6 | |
| 14 | 2018 | 5 | |
| 15 | 2018 | 4 | |
| 16 | 2018 | 4 | |
| 17 | 2025 | 3 | |
| 18 | 2010 | 2 | |
| 19 | 2022 | 2 | |
| 20 | 2013 | 2 |
About Ji Eun Oh
Ji Eun Oh is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Biomedical Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 29 papers that have together received 332 indexed citations. Recurring topics across this work include Digital Radiography and Breast Imaging (9 papers), Radiomics and Machine Learning in Medical Imaging (9 papers), Advanced X-ray and CT Imaging (6 papers), Medical Imaging Techniques and Applications (6 papers), Retinal Imaging and Analysis (3 papers), AI in cancer detection (3 papers), Advanced Neural Network Applications (2 papers) and Lung Cancer Diagnosis and Treatment (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (161 citations), Health Informatics (7 citations), Artificial Intelligence (97 citations), Genetics (26 citations) and Leadership and Management (3 citations). Ji Eun Oh has collaborated with scholars based in South Korea, United States and Germany. Frequent co-authors include Dae Kyung Sohn, Joohyung Lee, Kwang Gi Kim, Hee Jin Chang, Bo Yun Hur, Min Ju Kim, Jeong‐Min Hwang, Hee Kyung Yang, Hong‐Jun Yoon and Seonhye Lee. Their work appears in journals such as Journal of Digital Imaging, IEEE Access, Optics and Lasers in Engineering, Medicine and BioMed Research International.
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.